Ninth IEEE International
Conference on
Semantic Computing
Febraury 9-11, 2015
Anaheim, California, USA
http://www.ieee-icsc.org/
The field of Semantic Computing addresses the derivation of semantic information from content and the connection of semantics to knowledge, where "content" may be anything including structured data, video, audio, text, hardware, software, process, etc.
The Ninth IEEE International Conference on Semantic Computing (ICSC 2015) continues to foster the growth of a new research community. The conference builds on the success of the past ICSC conferences as an international forum for researchers and practitioners to present research that advances the state of the art and practice of Semantic Computing, as well as identifying emerging research topics and defining the future of the field. The event is located in Newport Beach, California at Hyatt Regency Newport Beach. The technical program of ICSC 2015 includes workshops, invited keynotes, paper presentations, panel discussions, industrial 'show and tells', demonstrations, and more. Submissions of high‐quality papers describing mature results or ongoing work are invited.
The main goal of the conference is to foster the dialog between experts in each sub‐discipline. Therefore we especially encourage submissions of work that is interesting to multiple areas, such as multimodal approaches.
Note: ICSC will be held in February from 2015.
SUBMISSIONS
Regular Papers, Short Papers, and Industry Papers.
Authors are invited to submit an 8-page (regular), 4-page (short), or 6‐page (industry) technical paper manuscript in double-column IEEE format following the guidelines available on the ICSC20104 web page.
Demonstration Papers and Posters.
Authors are invited to submit an 2-page (demonstration or poster) technical paper
manuscript in double-column IEEE format following the guidelines available on the
ICSC2014 web page.
Workshops Proposals.
The organizing committee invites proposals for workshops to be held in conjunction with the conference. These will focus on specific topics of the main conference. More information is available on the ICSC2014 web page.
The Conference Proceedings will be published by IEEE Computer Society Press. Distinguished quality papers presented at the conference will be selected for publication in internationally renowned journals.
AREAS OF INTEREST INCLUDE (but are not limited to):
Semantics based Analysis
Semantic Integration
Applications using Semantics
Semantic Interfaces
Febraury 9-11, 2015
Anaheim, California, USA
http://www.ieee-icsc.org/
The field of Semantic Computing addresses the derivation of semantic information from content and the connection of semantics to knowledge, where "content" may be anything including structured data, video, audio, text, hardware, software, process, etc.
The Ninth IEEE International Conference on Semantic Computing (ICSC 2015) continues to foster the growth of a new research community. The conference builds on the success of the past ICSC conferences as an international forum for researchers and practitioners to present research that advances the state of the art and practice of Semantic Computing, as well as identifying emerging research topics and defining the future of the field. The event is located in Newport Beach, California at Hyatt Regency Newport Beach. The technical program of ICSC 2015 includes workshops, invited keynotes, paper presentations, panel discussions, industrial 'show and tells', demonstrations, and more. Submissions of high‐quality papers describing mature results or ongoing work are invited.
The main goal of the conference is to foster the dialog between experts in each sub‐discipline. Therefore we especially encourage submissions of work that is interesting to multiple areas, such as multimodal approaches.
Note: ICSC will be held in February from 2015.
SUBMISSIONS
Regular Papers, Short Papers, and Industry Papers.
Authors are invited to submit an 8-page (regular), 4-page (short), or 6‐page (industry) technical paper manuscript in double-column IEEE format following the guidelines available on the ICSC20104 web page.
Demonstration Papers and Posters.
Authors are invited to submit an 2-page (demonstration or poster) technical paper
manuscript in double-column IEEE format following the guidelines available on the
ICSC2014 web page.
Workshops Proposals.
The organizing committee invites proposals for workshops to be held in conjunction with the conference. These will focus on specific topics of the main conference. More information is available on the ICSC2014 web page.
The Conference Proceedings will be published by IEEE Computer Society Press. Distinguished quality papers presented at the conference will be selected for publication in internationally renowned journals.
AREAS OF INTEREST INCLUDE (but are not limited to):
Semantics based Analysis
- Natural
language processing
- Image
and video analysis
- Audio,
music and speech analysis
- Data
and web mining
- Behavior
of software, systems, and networks
- Services
and networks
- Security
- Privacy
- Analysis
of social networks
Semantic Integration
- Metadata
and other description languages
- Database
schema integration
- Ontology
integration
- Interoperability
and service integration
- Semantic
programming languages and software engineering
- Semantic
system design and synthesis
Applications using Semantics
- Big
Data
- Search
engines and question answering
- Semantic
web services
- Content-based
multimedia retrieval and editing
- Context-aware
networks of sensors, devices and applications
- Devices
and applications
- Digital
library applications
- Machine
translation
- Music
description and meta-creation
- Medicine
and Biology
- GIS
systems and architecture
Semantic Interfaces
- Natural
language interfaces
- Multimodal
interfaces and mediation technology
- Human
centered computing
Important
Dates:
- Dec
15th, 2013: Workshop Proposals
- Feb
15th, 2014 (midnight, PST): Regular/Short/Poster/Demo
Paper Submission
- Feb
15th, 2014 (midnight, PST): Industry Paper
Submission
- TBD:
Notification Date
- TBD:
Camera-Ready & Registration
- June
16th-18th, 2014: Conference
Organizing Committee
General Co-Chairs
Abha Moitra, GE Research, USA
Phillip Sheu, University of California, Irvine, USA
Program Co-Chairs
Robert Mertens, HSW University of Applied Sciences, Hamelin, Germany
Giovanni Pilato, Italian National Research Council, Italy
Mei-Ling Shyu, University of Miami, USA
Nadine Steinmetz, HPI, Germany
Workshop Co-Chairs
Joseph Barr, San Diego State University, USA
Shu-Ching Chen, Florida International University, USA
Lars Knipping, Berlin Institute of Technology, Germany
Newton Lee, IFERS, USA
Joanne Luciano, University of California, Irvine, USA
Industry Co-Chairs
Barbara Starr, SemanticFuse, USA
Tong Zhang, HP Labs, USA
Panel Co-Chairs
Brian Harrington, University of Toronto, Canada
David Ostrowski, Ford, USA
Demo Co-Chair
Anne Hunt, Otto, Inc.
Publicity Co-Chairs (Tentative)
Jeffrey Abbott, Del Rey Systems, USA
Keith Chan, Hong Kong Polytech University
Brian Harrington, University of Toronto, Canada
Wolfgang H�rst, Utrecht University, The Netherlands
Wooju Kim, Yonsei University, Korea
Yonghong Tian, Peking University, China
Atsuo Yoshitaka, JAIST, Japan
Chengcui Zhang, University of Alabama at Birmingham, USA
Publication Co-Chairs
Jennifer Kim, University of California, Irvine, USA
Tao Meng, University of Miami, USA
Best Paper Award Co-Chairs
Gerald Friedland, ICSI Berkeley, USA
Roger Zimmermann, National University of Singapore
Finance and Local Arrangement Chair
Taehyung Wang, California State University Northridge, USA
Registration and Web Chair
Shaoting Wang, University of California, Irvine, USA
------------- Accepted Workshops ---------------------
Workshop on Semantic Computing for Computational Creativity (SCCC 2014)
The Third IEEE International Workshop on Semantic Multimedia (ICSC-SMM’14)
Tutorial and Workshop on Semantic Computing with Big Data (SCBD 2014)
The Third IEEE International Workshop on Data Science and Related Technologies (ICSC-DSRT’14)
CALL FOR WORKSHOP PROPOSALS
IEEE ICSC 2014: The Eighth IEEE International Conference on Semantic Computing June 16th- 18th, 2014, Newport Beach, California, USA
The IEEE ICSC 2014 organizing committee invites proposals for workshops to be held in conjunction with the conference.
The workshops will focus on specific topics of the main conference. The organizer(s) of approved workshops are responsible for advertising the workshop, distributing the call for papers, gathering submissions, and conducting the paper review process.
Any general questions regarding ICSC 2014 Workshops and workshop proposals should be directed to Prof. Shu-Ching Chen at chens@cs.fiu.edu .
Please add [ICSC2014-WS-Proposal] as subject.
Important Dates:
December 15, 2013: Workshop Proposals due
-------------------------------------------------------------
Note:
1. Every paper accepted for publication in the Proceedings of ICSC 2014 MUST be presented during the conference.
2. Every paper accepted for ICSC 2014 MUST have attached to it at least one registration at the full member/nonmember rate. Thus, for a paper for which all authors are students, one student author will be required to register at the full registration rate.
The Tenth IEEE International Workshop on Semantic
Computing for Social
Networks and Organization Sciences: from user information to social
knowledge (SCSN 2022)
http://pa.icar.cnr.it/scsn22
in conjunction with
16th IEEE International Conference on Semantic Computing (ICSC2022)
January 26-28, 2022,
As it is still not clear when U.S. and the world can be out of the pandemic, ICSC2022 will be fully virtual again.
http://pa.icar.cnr.it/scsn22
in conjunction with
16th IEEE International Conference on Semantic Computing (ICSC2022)
January 26-28, 2022,
As it is still not clear when U.S. and the world can be out of the pandemic, ICSC2022 will be fully virtual again.
| Overview | Topics of interest | Important Dates | Organizing Committee | Submission
Guidelines |
Call For Papers
Overview
------------
Internet
users have become providers of information through social networks like
Facebook, Twitter, Flickr, and so forth. On the other side
organisations may benefit by integrating social network analysis, for
instance, to understand employee innovative behaviour, as, for
instance, integrating social networks and the leader member exchange
perspectives. Still, networks models show how information sharing,
models of social cohesion and mutual goals (i.e. values) make
organization social capital. In this context Semantic Computing
plays a chief role because of its potentiality to turn shapeless crowds
information into social and digestible knowledge.
Furthermore, recent developments in processing, storing, and sharing huge amount of data become problematic due to the lack of new approaches, techniques, methods, algorithms and technologies oriented to social networks, including theoretical notions and insufficient awareness on security, retrieval, networking, behavioral and social issues.
The workshop, that will take place between Jan 26, 2022 - Jan 28, 2022, in conjunction with the 16th IEEE International Conference on Semantic Computing (ICSC2022), (http://www.ieee-icsc.org/) is a forum for researchers, industry practitioners and domain experts in the field of semantic computing, social networks, and social interactions and organisation sciences to exchange the latest advances in the state of the art and practice of semantic computing applications to the social network context.
Furthermore, recent developments in processing, storing, and sharing huge amount of data become problematic due to the lack of new approaches, techniques, methods, algorithms and technologies oriented to social networks, including theoretical notions and insufficient awareness on security, retrieval, networking, behavioral and social issues.
The workshop, that will take place between Jan 26, 2022 - Jan 28, 2022, in conjunction with the 16th IEEE International Conference on Semantic Computing (ICSC2022), (http://www.ieee-icsc.org/) is a forum for researchers, industry practitioners and domain experts in the field of semantic computing, social networks, and social interactions and organisation sciences to exchange the latest advances in the state of the art and practice of semantic computing applications to the social network context.
Topics of interest
----------------------
The topics of interest of the workshop include, but are not limited to:
- Semantics-driven indexing and retrieval for Social Media
- User modeling or social profiling for business and/or non profit organizations
- Semantics-based recommender systems for Social Media: is the dream coming true?
- Web adaptation methods and techniques
- Content on demand: customization or personalization?
- Semantic context modeling and extraction
- Semantic Models generation from social networks data
- Semantically-enabled data filtering
- Sentiment analysis in Social Networks
- Opinion mining in Social Networks
- Social Web Mining
- Semantics of Collective Intelligence
- Mobile social networking
- Distributed semantic computing for social network data analysis
- Collaborative filtering, mining and prediction
- Social computing applications and case studies
- Social Data
- Social Networking
- Data Science and Big Data
- Data Security
- Security Risk Analysis, Modelling, Evaluation and Management
- Social Media Analytics
- Privacy
- Recent Theory, Trends, Technologies and Applications
- Future Directions and Challenges in Information Security System
- Effects of social relationships and knowledge on organisation innovative behaviour
- Emerging social values and their impact on organisation leaderships
Important Dates
--------------------
(optiona) Abstract Submission Deadline:(extended) November 26, 2021
Submission Deadline: (extended) December 3, 2021 PST
Camera-Ready Submission and Registration Deadline: (extended) December 12, 2021 PST
Organizing Committee
-----------------------------
Shady Khalil, Texas A&M University, Qatar
Jianquan Liu, NEC, Japan
Giovanni Pilato, Italian National Research Council, Italy
TPC (in progress)
----------------------------
Ankur Bist Govind ballabh Pant university of agri. and tech., India
Erdogan Dogdu TOBB University of Economics and Technology, Turkey
Chason Fu Ishiguro Lab, Engineering Science, Osaka University, Japan
Sedef Gunduz, Gazi University, Ankara, Turkey
Jason Jung, Chung-Ang University, South Korea
Mahmut Kaya, Siirt University, Turkey
Fazel Keshtkar, St. John's University, United States
Takahiro Komamizu Nagoya University, Japan
Adam Krzyzak,Concordia University, Canada
Marco La Cascia University of Palermo, Italy
Zheng Liu Nanjing University of Posts and Telecommunications. China
Giosue' Lo Bosco University of Palermo, Italy
Andreas Nuernberger Otto-von-Guericke University of Magdeburg, Germany
Romualdo Pereira Junior, Center for Research on Architecture of Information - CPAI - UnB, Brazil
Jun Shen, University of Wollongong, Australia
Xufei Wang, Arizona State University, United States
Christian Winkler, Datanizing GmbH, Germany
Alexey Averkin Dorodnicyn Computing Center of RAN
Wookey Lee Inha University
Fadi Muheidat California State University San Bernardino, CSUSB
Murat Ozbayoglu TOBB University of Economics and Technology
Seref Sagiroglu Gazi University
Daniele Schicchi University of Palermo
Kai Shu Arizona State University
Nicolas Turenne INRA UPEM
Filippo Vella National Research Council of Italy
Chaokun Wang Tsinghua University
Liang Wu Airbnb, Inc.
Sergey Yarushev Plekhanov Russian University of Economics
Feida Zhu Singapore Management University
Submission Guidelines
----------------------------
Manuscripts
must be written (6 pages maximum, all included) in English and follow
the instructions in the Manuscript Formatting and Templates page given
in ICSC 2022 website (http://www.ieee-icsc.org/)
at the “Submission” section. The papers may be submitted without submitting an abstract first.
Papers must be original and not be submitted to or accepted by any other conference or journal.
Only electronic submission will be accepted. Technical paper authors MUST submit their manuscripts through EasyChair ( https://easychair.org/conferences/?conf=scsn22), by following the instructions given on the SCSN website (http://pa.icar.cnr.it/scsn22/).
Manuscripts may only be submitted in PDF format.
Each paper will be peer-reviewed. Papers accepted by the workshop will be published in the conference proceedings published by IEEE Computer Society Press.
Authors are encouraged to submit an abstract (before the abstract submission deadline) and update the abstract to a full paper before the deadline of full paper submission.
For any question regarding the workshop please contact the organizers at scsn-ws (at) pa.icar.cnr.it
http://www.ieee-icsc.org/
Papers must be original and not be submitted to or accepted by any other conference or journal.
Only electronic submission will be accepted. Technical paper authors MUST submit their manuscripts through EasyChair ( https://easychair.org/conferences/?conf=scsn22), by following the instructions given on the SCSN website (http://pa.icar.cnr.it/scsn22/).
Manuscripts may only be submitted in PDF format.
Each paper will be peer-reviewed. Papers accepted by the workshop will be published in the conference proceedings published by IEEE Computer Society Press.
Authors are encouraged to submit an abstract (before the abstract submission deadline) and update the abstract to a full paper before the deadline of full paper submission.
For any question regarding the workshop please contact the organizers at scsn-ws (at) pa.icar.cnr.it
http://www.ieee-icsc.org/
The conference will take place at the
University Center of CMU – west of the stadium
Campus Map
Travel:
http://www.cmu.edu/about/visit/directions-parking.shtml
Pittsburgh Airport Flyer:
http://www.portauthority.org/PAAC/tabid/241/default.aspx
Keynotes
keynote
keynote
keynote
keynote
The Roles of Reductionism,
Emergence and Functional Equivalence in Semantic Computing
by Stephen E. Levinson,
Department of Electrical and Computer Engineering and the Beckman Institute, University of Illinois at Urbana-Champaign
Abstract
Speaker Bio
by Stephen E. Levinson,
Department of Electrical and Computer Engineering and the Beckman Institute, University of Illinois at Urbana-Champaign
Abstract
Speaker Bio
Meta-Algorithmic Approaches to Semantic Computing
by Steve Simske,
HP Labs
Semantic computing is concerned with the combination of semantic analysis, natural language processing, and data mining approaches to provide machine understanding for a variety of applications. This includes the automatic processing of user intentions, deriving meaning from media, and intelligently mapping user intentions to important downstream tasks such as search, retrieval, information management, and information re-purposing/mashing. Each of these tasks can uniquely benefit from a meta-algorithmic approach.
Meta-algorithmics are a set of more than 20 parallel processing patterns that, combined, offer a set of approaches to building optimized intelligent systems. Specific meta-algorithmic patterns, along with a fully generalized hybrid pattern, allow any intelligent system architect to build robust, accurate and cost- sensitive intelligent systems. Meta-algorithmic patterns range from simpler first-order patterns such as Voting and Predictive Selection to highly-complex third order patterns such as Expert Feedback to provide a repertoire of means to use two or more algorithms, systems or intelligence engines to create better systems. Meta-algorithmics take advantage of the convergent ubiquity of cloud computing, massively parallel processing, and inexpensive storage to afford previously unimaginable data analysis approaches. In this talk, the application of meta-algorithmic approaches to various semantic computing challenges – particular those in categorization, classification, summarization, search, and authentication – will be described. Meta-algorithmics will be shown to provide a third major form of parallel processing (supplementing parallelism by task and by component) to semantic computing scientists, and a new toolkit for improving intelligent system performance.
back to keynotes
by Steve Simske,
HP Labs
Semantic computing is concerned with the combination of semantic analysis, natural language processing, and data mining approaches to provide machine understanding for a variety of applications. This includes the automatic processing of user intentions, deriving meaning from media, and intelligently mapping user intentions to important downstream tasks such as search, retrieval, information management, and information re-purposing/mashing. Each of these tasks can uniquely benefit from a meta-algorithmic approach.
Meta-algorithmics are a set of more than 20 parallel processing patterns that, combined, offer a set of approaches to building optimized intelligent systems. Specific meta-algorithmic patterns, along with a fully generalized hybrid pattern, allow any intelligent system architect to build robust, accurate and cost- sensitive intelligent systems. Meta-algorithmic patterns range from simpler first-order patterns such as Voting and Predictive Selection to highly-complex third order patterns such as Expert Feedback to provide a repertoire of means to use two or more algorithms, systems or intelligence engines to create better systems. Meta-algorithmics take advantage of the convergent ubiquity of cloud computing, massively parallel processing, and inexpensive storage to afford previously unimaginable data analysis approaches. In this talk, the application of meta-algorithmic approaches to various semantic computing challenges – particular those in categorization, classification, summarization, search, and authentication – will be described. Meta-algorithmics will be shown to provide a third major form of parallel processing (supplementing parallelism by task and by component) to semantic computing scientists, and a new toolkit for improving intelligent system performance.
back to keynotes
Steve Simske
HP Labs
Steve Simske is the Director and Chief Technologist for the Content Solutions Lab in HP Labs. His research areas include image processing, image analysis and document understanding technologies ranging from automatic book digitization to and speech recognition. Steve developed the toolset for architecting massive intelligent systems - meta-algorithmics – which affords the combination of two or more intelligent systems to create more robust, accurate and often faster larger systems, or “ecosystems”. This culminated in the recent book, “Meta-Algorithmics” (Wiley & Sons). Steve has earlier worked on medical signal processing for portable medicine, including novel means of reducing biological noise in electrocardiograms (ECGs). Steve created HP’s Security Printing and Imaging program - image analysis, security, analytics and forensics to prevent counterfeiting, protect branded products, and provide investigative support for anti-fraud. This led in part to his invitation to participate as a Member of the World Economic Forum Global Agenda Council on Illicit Trade and Organized Crime for the past four years. Steve is an HP Fellow and has more than 75 US Patents and more than 300 peer-reviewed publications.
back to keynotes
HP Labs
Steve Simske is the Director and Chief Technologist for the Content Solutions Lab in HP Labs. His research areas include image processing, image analysis and document understanding technologies ranging from automatic book digitization to and speech recognition. Steve developed the toolset for architecting massive intelligent systems - meta-algorithmics – which affords the combination of two or more intelligent systems to create more robust, accurate and often faster larger systems, or “ecosystems”. This culminated in the recent book, “Meta-Algorithmics” (Wiley & Sons). Steve has earlier worked on medical signal processing for portable medicine, including novel means of reducing biological noise in electrocardiograms (ECGs). Steve created HP’s Security Printing and Imaging program - image analysis, security, analytics and forensics to prevent counterfeiting, protect branded products, and provide investigative support for anti-fraud. This led in part to his invitation to participate as a Member of the World Economic Forum Global Agenda Council on Illicit Trade and Organized Crime for the past four years. Steve is an HP Fellow and has more than 75 US Patents and more than 300 peer-reviewed publications.
back to keynotes
The
Roles of Reductionism, Emergence and Functional Equivalence in Semantic
Computing
Stephen E. Levinson,
Department of Electrical and Computer Engineering and the Beckman Institute
University of Illinois at Urbana-Champaign
selevins@illinois.edu
In 1950 Albert Einstein addressed the International College of Surgeons. With appropriate humility he insisted that all human mental activity ultimately rests on physics. Twenty-five years ago, the Beckman Institute was conceived as an interdisciplinary laboratory dedicated to the study of human cognition by the cooperative efforts of the physical, biological and social sciences.
Cognitive learning is a complex phenomenon peculiar to humans and, to a lesser extent, higher animals. Since learning is mediated by the central nervous system, its study by qualitative and empirical methods has traditionally been the province of neurobiology and psychology. More recently analogies to natural learning have been drawn to certain information processing technologies including computing, robotics, machine vision and automatic speech recognition in which context it has been treated by appeal to detailed abstract (i. e. non-biological) mathematical models. For historical and organizational reasons, the two approaches are pursued virtually independently. As biology and psychology are becoming more quantitative, this is a propitious time to undertake an interdisciplinary project in which the development of large scale mathematical models is critically informed by known biological and psychological principles. Conversely, the abstract models thus generated should be sufficiently rich to make to make predictions about human behavior that can be evaluated by experiments on anthropomorphic robots. The goal is the construction of a detailed quantitative model and a set of formal organizing principles that together constitute a theory of cognition.
For more than fifteen years, the language acquisition and robotics lab at the Beckman institute has followed precisely this path. We begin with Einstein's reductionist hypothesis tempered by the notions of emergence derived from Gibbs' statistical mechanics and Shannon's information theoretic interpretation. Also invoked are ideas about functional equivalence expressed by Turing's model of thought as formal computation, Wiener's model of homeostasis as stochastic adaptive control and von Neumann's characterization of behavior as utility maximization in social games. Our work is not about robotics or speech or vision. It is about all of them working together to produce intelligent behavior because, we believe, cognitive functions do not exist in isolation and there is no such thing as a disembodied mind. As a cognitive model of reality is acquired, a linguistic image of it is formed primarily in response to sensorimotor perception. When the language is fully acquired, most mental processes are mediated linguistically and we appear to think in our native language which we hear as our mind's voice.
Several examples are given of learned behavior including fine motor control tasks and language acquisition.
back to keynotes
Stephen E. Levinson,
Department of Electrical and Computer Engineering and the Beckman Institute
University of Illinois at Urbana-Champaign
selevins@illinois.edu
In 1950 Albert Einstein addressed the International College of Surgeons. With appropriate humility he insisted that all human mental activity ultimately rests on physics. Twenty-five years ago, the Beckman Institute was conceived as an interdisciplinary laboratory dedicated to the study of human cognition by the cooperative efforts of the physical, biological and social sciences.
Cognitive learning is a complex phenomenon peculiar to humans and, to a lesser extent, higher animals. Since learning is mediated by the central nervous system, its study by qualitative and empirical methods has traditionally been the province of neurobiology and psychology. More recently analogies to natural learning have been drawn to certain information processing technologies including computing, robotics, machine vision and automatic speech recognition in which context it has been treated by appeal to detailed abstract (i. e. non-biological) mathematical models. For historical and organizational reasons, the two approaches are pursued virtually independently. As biology and psychology are becoming more quantitative, this is a propitious time to undertake an interdisciplinary project in which the development of large scale mathematical models is critically informed by known biological and psychological principles. Conversely, the abstract models thus generated should be sufficiently rich to make to make predictions about human behavior that can be evaluated by experiments on anthropomorphic robots. The goal is the construction of a detailed quantitative model and a set of formal organizing principles that together constitute a theory of cognition.
For more than fifteen years, the language acquisition and robotics lab at the Beckman institute has followed precisely this path. We begin with Einstein's reductionist hypothesis tempered by the notions of emergence derived from Gibbs' statistical mechanics and Shannon's information theoretic interpretation. Also invoked are ideas about functional equivalence expressed by Turing's model of thought as formal computation, Wiener's model of homeostasis as stochastic adaptive control and von Neumann's characterization of behavior as utility maximization in social games. Our work is not about robotics or speech or vision. It is about all of them working together to produce intelligent behavior because, we believe, cognitive functions do not exist in isolation and there is no such thing as a disembodied mind. As a cognitive model of reality is acquired, a linguistic image of it is formed primarily in response to sensorimotor perception. When the language is fully acquired, most mental processes are mediated linguistically and we appear to think in our native language which we hear as our mind's voice.
Several examples are given of learned behavior including fine motor control tasks and language acquisition.
back to keynotes
Stephen E. Levinson
Department of Electrical and Computer Engineering and the Beckman Institute
University of Illinois at Urbana-Champaign
Stephen E. Levinson was born in New York City on September 27, 1944. He received the B. A. degree in Engineering Sciences from Harvard in 1966, and the M. S. and Ph.D. degrees in Electrical Engineering from the University of Rhode Island, Kingston, Rhode Island in 1972 and 1974, respectively. From 1966-1969 he was a design engineer at Electric Boat Division of General Dynamics in Groton, Connecticut. From 1974-1976 he held a J. Willard Gibbs Instructorship in Computer Science at Yale University. In 1976, he joined the technical staff of Bell Laboratories in Murray Hill, NJ where he conducted research in the areas of speech recognition and understanding. In 1979 he was a visiting researcher at the NTT Musashino Electrical Communication Laboratory in Tokyo, Japan. In 1984, he held a visiting fellowship in the Engineering Department at Cambridge University. In 1990, Dr. Levinson became head of the Linguistics Research Department at AT&T Bell Laboratories where he directed research in Speech Synthesis, Speech Recognition and Spoken Language Translation. In 1997, he joined the Department of Electrical and Computer Engineering of the University of Illinois at Urbana-Champaign where he teaches courses in Speech and Language Processing and leads research projects in speech synthesis and automatic language acquisition. He is also a full-time faculty member of the Beckman Institute for Advanced Science and Technology where he serves as the head of the Artificial Intelligence group. Dr. Levinson is a member of the Association for Computing Machinery, a fellow of the Institute of Electrical and Electronic Engineers and a fellow of the Acoustical Society of America. He is a founding editor of the journal Computer Speech and Language and a former member and chair of the Industrial Advisory Board of the CAIP Center at Rutgers University. He is the author of more than 100 technical papers and holds seven patents. His book, published in 2005 by John Wiley and Sons, Ltd., is entitled "Mathematical Models for Speech Technology"
back to keynotes
Department of Electrical and Computer Engineering and the Beckman Institute
University of Illinois at Urbana-Champaign
Stephen E. Levinson was born in New York City on September 27, 1944. He received the B. A. degree in Engineering Sciences from Harvard in 1966, and the M. S. and Ph.D. degrees in Electrical Engineering from the University of Rhode Island, Kingston, Rhode Island in 1972 and 1974, respectively. From 1966-1969 he was a design engineer at Electric Boat Division of General Dynamics in Groton, Connecticut. From 1974-1976 he held a J. Willard Gibbs Instructorship in Computer Science at Yale University. In 1976, he joined the technical staff of Bell Laboratories in Murray Hill, NJ where he conducted research in the areas of speech recognition and understanding. In 1979 he was a visiting researcher at the NTT Musashino Electrical Communication Laboratory in Tokyo, Japan. In 1984, he held a visiting fellowship in the Engineering Department at Cambridge University. In 1990, Dr. Levinson became head of the Linguistics Research Department at AT&T Bell Laboratories where he directed research in Speech Synthesis, Speech Recognition and Spoken Language Translation. In 1997, he joined the Department of Electrical and Computer Engineering of the University of Illinois at Urbana-Champaign where he teaches courses in Speech and Language Processing and leads research projects in speech synthesis and automatic language acquisition. He is also a full-time faculty member of the Beckman Institute for Advanced Science and Technology where he serves as the head of the Artificial Intelligence group. Dr. Levinson is a member of the Association for Computing Machinery, a fellow of the Institute of Electrical and Electronic Engineers and a fellow of the Acoustical Society of America. He is a founding editor of the journal Computer Speech and Language and a former member and chair of the Industrial Advisory Board of the CAIP Center at Rutgers University. He is the author of more than 100 technical papers and holds seven patents. His book, published in 2005 by John Wiley and Sons, Ltd., is entitled "Mathematical Models for Speech Technology"
back to keynotes
Complex
event handling with Semantic Technology
by Jans Aasman,
Franz Inc.
Enterprises collect large bodies of data that describe interactions between their customers. Think of phone calls, text messages, financial transactions, auctions, emails, etc. Each of these interactions can be described as an event object with two or more actors, a start time and possibly an end-time, almost always an location and then other properties to describe the event. A collection of events will inevitably result in a large graph on which we can do interesting computations that include graph analytics, geospatial and temporal reasoning. Relational databases are fundamentally unfit to explore the graph within these networks and Big Data solutions (Hadoop, etc) are usually not meant to work with sparse graphs, rules and geospatial and temporal reasoning. The maturing capabilities of RDF Graph Databases have made them the optimal approach to mine these networks that have temporal and geospatial features. This presentation will discuss an application of Semantic Graph Mining using anonymized information from an on-line bank in Asia. The data includes all payments from account to account along with details about links to each other through IP addresses, goods traded, location, etc. We will show how we can detect, in real time, whether an account executing a transaction is part of a group of accounts that is somehow linked to fraudulent activity.
back to keynotes
by Jans Aasman,
Franz Inc.
Enterprises collect large bodies of data that describe interactions between their customers. Think of phone calls, text messages, financial transactions, auctions, emails, etc. Each of these interactions can be described as an event object with two or more actors, a start time and possibly an end-time, almost always an location and then other properties to describe the event. A collection of events will inevitably result in a large graph on which we can do interesting computations that include graph analytics, geospatial and temporal reasoning. Relational databases are fundamentally unfit to explore the graph within these networks and Big Data solutions (Hadoop, etc) are usually not meant to work with sparse graphs, rules and geospatial and temporal reasoning. The maturing capabilities of RDF Graph Databases have made them the optimal approach to mine these networks that have temporal and geospatial features. This presentation will discuss an application of Semantic Graph Mining using anonymized information from an on-line bank in Asia. The data includes all payments from account to account along with details about links to each other through IP addresses, goods traded, location, etc. We will show how we can detect, in real time, whether an account executing a transaction is part of a group of accounts that is somehow linked to fraudulent activity.
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Jans Aasman
Franz Inc.
Dr. Jans Aasman started his career as an experimental and cognitive psychologist, earning his PhD in cognitive science with a detailed model of car driver behaviorr. He has spent most of his professional life in telecommunications research, specializing in intelligent user interfaces and applied artificial intelligence projects. From 1995 to 2004, he was also a part-time professor in the Industrial Design department of the Technical University of Delft. Jans is currently the CEO of Franz Inc., the leading supplier of commercial, persistent, and scalable RDF database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Semantic Web applications.
Dr. Aasman has gained notoriety as a conference speaker at such events as Semantic Technologies Conference, International Semantic Web Conference, Java One, Enterprise Data World, Semantics in Healthcare and Life Sciences, Linked Data Planet, INSA, GeoWeb, AAAI, NoSQLNow, Graph Data Management, RuleML, IEEE conferences, and DEBS to name a few.
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Franz Inc.
Dr. Jans Aasman started his career as an experimental and cognitive psychologist, earning his PhD in cognitive science with a detailed model of car driver behaviorr. He has spent most of his professional life in telecommunications research, specializing in intelligent user interfaces and applied artificial intelligence projects. From 1995 to 2004, he was also a part-time professor in the Industrial Design department of the Technical University of Delft. Jans is currently the CEO of Franz Inc., the leading supplier of commercial, persistent, and scalable RDF database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Semantic Web applications.
Dr. Aasman has gained notoriety as a conference speaker at such events as Semantic Technologies Conference, International Semantic Web Conference, Java One, Enterprise Data World, Semantics in Healthcare and Life Sciences, Linked Data Planet, INSA, GeoWeb, AAAI, NoSQLNow, Graph Data Management, RuleML, IEEE conferences, and DEBS to name a few.
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A
“Kansei” Multimedia Computing System for Environmental Analysis and
Cross-Cultural Communication
by Yasushi Kiyoki,
Graduate School of Media and Governance, Keio University
In the design of multimedia computing systems, one of the most important issues is how to search and analyze media data (images, music, movies and documents), according to user's impressions and contexts. We introduce a "Kansei" and semantic associative search method based on the “Mathematical Model of Meaning (MMM)”. The concept of "Kansei" includes several meanings on sensitive recognition, such as “emotion”, "impression", "human senses", "feelings", "sensitivity", "psychological reaction" and "physiological reaction". This model realizes "Kansei" processing and semantic associative search for media data, according to user's impressions and contexts and is applied to compute semantic correlations between keywords, images, music movies and documents dynamically in a context-dependent way. The main feature of our system based on this model is to realize semantic associative search in the 2000 dimensional orthogonal semantic space with semantic projection functions. This space is created for dynamically computing semantic equivalence or similarity between keywords and media data.
We have designed "Kansei-Multimedia Computing System” for realizing international and collaborative research environments, as a new platform of multimedia semantic computing system. This system consists of two subsystems: (1) “Kansei” image and music search and analysis system for cooperative creation and manipulation of multimedia objects and (2) Cross-cultural Collaboration System with images databases.
As an important global environmental system, we have also designed a multimedia semantic computing system for global environmental analysis. One of the important applications of this system is “Global Environment-Analysis,” which aims to evaluate various influences caused by natural disasters in global environments. Our experimental results have shown the feasibility and effectiveness of our semantic associative computing system based on “MMM” in global environmental analyses.
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by Yasushi Kiyoki,
Graduate School of Media and Governance, Keio University
In the design of multimedia computing systems, one of the most important issues is how to search and analyze media data (images, music, movies and documents), according to user's impressions and contexts. We introduce a "Kansei" and semantic associative search method based on the “Mathematical Model of Meaning (MMM)”. The concept of "Kansei" includes several meanings on sensitive recognition, such as “emotion”, "impression", "human senses", "feelings", "sensitivity", "psychological reaction" and "physiological reaction". This model realizes "Kansei" processing and semantic associative search for media data, according to user's impressions and contexts and is applied to compute semantic correlations between keywords, images, music movies and documents dynamically in a context-dependent way. The main feature of our system based on this model is to realize semantic associative search in the 2000 dimensional orthogonal semantic space with semantic projection functions. This space is created for dynamically computing semantic equivalence or similarity between keywords and media data.
We have designed "Kansei-Multimedia Computing System” for realizing international and collaborative research environments, as a new platform of multimedia semantic computing system. This system consists of two subsystems: (1) “Kansei” image and music search and analysis system for cooperative creation and manipulation of multimedia objects and (2) Cross-cultural Collaboration System with images databases.
As an important global environmental system, we have also designed a multimedia semantic computing system for global environmental analysis. One of the important applications of this system is “Global Environment-Analysis,” which aims to evaluate various influences caused by natural disasters in global environments. Our experimental results have shown the feasibility and effectiveness of our semantic associative computing system based on “MMM” in global environmental analyses.
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Challenges
at the Intersection of Semantic Computing with Law, Legal Reasoning,
and Legal Practice
by Kevin D. Ashley
University of Pittsburgh
This talk will briefly consider the intersection of semantic computing with law, legal reasoning, and legal practice. Based on the definition of semantic computing in the materials for the fourth IEEE International Conference on Semantic Computing (ICSC2010), the intersection of semantic computing with law, legal reasoning, and legal practice addresses the derivation and matching of the semantics of computational content to that of naturally expressed user intentions relating to legal problem-solving or analysis in order to retrieve, manage, manipulate or create content based on its significance to the legal problem-solving or analysis, where "content" includes text, video, audio, services, networks, etc.
The talk will illustrate some challenges of addressing the pressing needs for new ways to relate the semantics of computational content to users’ intentions relating to legal problem-solving or analysis. The needs are inherent in many developments in high tech legal practice, e-government, and research in Artificial Intelligence and Law. For example:
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by Kevin D. Ashley
University of Pittsburgh
This talk will briefly consider the intersection of semantic computing with law, legal reasoning, and legal practice. Based on the definition of semantic computing in the materials for the fourth IEEE International Conference on Semantic Computing (ICSC2010), the intersection of semantic computing with law, legal reasoning, and legal practice addresses the derivation and matching of the semantics of computational content to that of naturally expressed user intentions relating to legal problem-solving or analysis in order to retrieve, manage, manipulate or create content based on its significance to the legal problem-solving or analysis, where "content" includes text, video, audio, services, networks, etc.
The talk will illustrate some challenges of addressing the pressing needs for new ways to relate the semantics of computational content to users’ intentions relating to legal problem-solving or analysis. The needs are inherent in many developments in high tech legal practice, e-government, and research in Artificial Intelligence and Law. For example:
- In
evidentiary discovery, the need to process enormous numbers of
electronic documents in terms of their meaning and significance
relative to litigators’ intentions concerning clients’ legal claims and
strategies
- In
business compliance, the need to relate computationally-manipulable
norms to regulators’ intentions embodied in the natural language legal
codes the norms are meant to represent and implement and in the
principles and policies underlying the regulations
- In
legal information retrieval and modeling legal reasoning, the need to
relate computationally-processable ontological representations of legal
concepts and their meanings to the intentions of legal researchers and
users in retrieving, comparing, and drawing inferences from relevant
legal rules, cases, and commentaries
- In
e-Commerce and semantic web-based legal services, the need to relate
computationally-accessible resources to the intentions of
electronically contracting parties
- In
automated rights management of privacy and intellectual property rights
in data, the need to relate proposed data access to the intentions of
data rights owners and users
- In
e-government and legal education, the need to relate
computationally-processable argument diagrams and the meanings and
intentions of legal arguers.
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Yasushi Kiyoki
Graduate School of Media and Governance, Keio University
Yasushi Kiyoki received his B.E., M.E. and Ph.D. degrees in electrical engineering from Keio University in 1978, 1980 and 1983, respectively. From 1984 to 1996, he was with Institute of Information Sciences and Electronics, Univ. of Tsukuba, as an assistant professor and then an associate professor. Since 1996, he has been with Graduate School of Media and Governance, where he is currently a professor. His research addresses multi-database systems, knowledge base systems, semantic associative processing, and multimedia database systems. He serves as the editor-in-chief on Information Modeling and Knowledge Bases (IOS Press). He also served program chairs for several international conferences, such as 7th International Conference on Database Systems for Advanced Applications and European-Japanese Conferences on Information Modeling and Knowledge bases (2004-Present).
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Graduate School of Media and Governance, Keio University
Yasushi Kiyoki received his B.E., M.E. and Ph.D. degrees in electrical engineering from Keio University in 1978, 1980 and 1983, respectively. From 1984 to 1996, he was with Institute of Information Sciences and Electronics, Univ. of Tsukuba, as an assistant professor and then an associate professor. Since 1996, he has been with Graduate School of Media and Governance, where he is currently a professor. His research addresses multi-database systems, knowledge base systems, semantic associative processing, and multimedia database systems. He serves as the editor-in-chief on Information Modeling and Knowledge Bases (IOS Press). He also served program chairs for several international conferences, such as 7th International Conference on Database Systems for Advanced Applications and European-Japanese Conferences on Information Modeling and Knowledge bases (2004-Present).
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Kevin D. Ashley
Professor of Law and Intelligent Systems
University of Pittsburgh
Dr. Kevin Ashley holds interdisciplinary appointments as a faculty member of the Graduate Program in Intelligent Systems at the University of Pittsburgh, a Senior Scientist at the Learning Research and Development Center, a Professor of Law, and Adjunct Professor of Computer Science. He received a B.A. in philosophy (magna cum laude) from Princeton University in 1973, J.D. (cum laude) from Harvard Law School in 1976, and Ph.D. in computer science in 1988 from the University of Massachusetts.
An expert on computer modeling of legal reasoning and cyberspace legal issues, he has reported his research in conference proceedings of the American Association for Artificial Intelligence, the International Association for Artificial Intelligence and the Law, and the Cognitive Science Society. He has also published in journals such as Jurimetrics, IEEE Expert, International Journal of Man/Machine Studies, and Journal of Artificial Intelligence and the Law, of which he is an editor. Professor Ashley has been a Principal Investigator of a number of National Science Foundation grants to study reasoning with cases in law and professional ethics. Professor Ashley is also author of Modeling Legal Argument: Reasoning with Cases and Hypotheticals (MIT Press/Bradford Books, 1990).
A former National Science Foundation Presidential Young Investigator, Professor Ashley was also a visiting scientist at the IBM Thomas J. Watson Research Center, and a recipient of an IBM Graduate Research Fellowship. He is a Fellow of the American Association for Artificial Intelligence, and a past President of the International Association of Artificial Intelligence and Law.
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Professor of Law and Intelligent Systems
University of Pittsburgh
Dr. Kevin Ashley holds interdisciplinary appointments as a faculty member of the Graduate Program in Intelligent Systems at the University of Pittsburgh, a Senior Scientist at the Learning Research and Development Center, a Professor of Law, and Adjunct Professor of Computer Science. He received a B.A. in philosophy (magna cum laude) from Princeton University in 1973, J.D. (cum laude) from Harvard Law School in 1976, and Ph.D. in computer science in 1988 from the University of Massachusetts.
An expert on computer modeling of legal reasoning and cyberspace legal issues, he has reported his research in conference proceedings of the American Association for Artificial Intelligence, the International Association for Artificial Intelligence and the Law, and the Cognitive Science Society. He has also published in journals such as Jurimetrics, IEEE Expert, International Journal of Man/Machine Studies, and Journal of Artificial Intelligence and the Law, of which he is an editor. Professor Ashley has been a Principal Investigator of a number of National Science Foundation grants to study reasoning with cases in law and professional ethics. Professor Ashley is also author of Modeling Legal Argument: Reasoning with Cases and Hypotheticals (MIT Press/Bradford Books, 1990).
A former National Science Foundation Presidential Young Investigator, Professor Ashley was also a visiting scientist at the IBM Thomas J. Watson Research Center, and a recipient of an IBM Graduate Research Fellowship. He is a Fellow of the American Association for Artificial Intelligence, and a past President of the International Association of Artificial Intelligence and Law.
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Bhavani
Thuraisingham
Professor
University of Texas, Dallas
Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. I Distinguished Professor in the Erik Jonsson School of Engineering and Computer Science at the University of Texas at Dallas (UTD) effective September 2010. She joined UTD in October 2004 as a Professor of Computer Science and Director of the Cyber Security Research Center which conducts research in data security and privacy, secure networks, secure languages, secure social media, data mining and semantic web. She is an elected Fellow of three prestigious organizations: the IEEE (Institute for Electrical and Electronics Engineers), the AAAS (American Association for the Advancement of Science) and the BCS (British Computer Society). She is the recipient of numerous awards including the IEEE Computer Society’s 1997 Technical Achievement Award for “outstanding and innovative contributions to secure data management” and the 2010 Research Leadership Award for Outstanding and Sustained Leadership Contributions to the field of Intelligence and Security Informatics” presented jointly by the IEEE Intelligent and Transportation Systems Society Technical Committee on Intelligence and Security Informatics in Transportation Systems and the IEEE Systems, Man and Cybernetics Society Technical Committee on Homeland Security. She served as served as an IEEE Distinguished Lecturer between 2002 and 2005. She was also quoted by Silicon India magazine as one of the seven leading technology innovators of South Asian origin in the USA in 2002.
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Professor
University of Texas, Dallas
Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. I Distinguished Professor in the Erik Jonsson School of Engineering and Computer Science at the University of Texas at Dallas (UTD) effective September 2010. She joined UTD in October 2004 as a Professor of Computer Science and Director of the Cyber Security Research Center which conducts research in data security and privacy, secure networks, secure languages, secure social media, data mining and semantic web. She is an elected Fellow of three prestigious organizations: the IEEE (Institute for Electrical and Electronics Engineers), the AAAS (American Association for the Advancement of Science) and the BCS (British Computer Society). She is the recipient of numerous awards including the IEEE Computer Society’s 1997 Technical Achievement Award for “outstanding and innovative contributions to secure data management” and the 2010 Research Leadership Award for Outstanding and Sustained Leadership Contributions to the field of Intelligence and Security Informatics” presented jointly by the IEEE Intelligent and Transportation Systems Society Technical Committee on Intelligence and Security Informatics in Transportation Systems and the IEEE Systems, Man and Cybernetics Society Technical Committee on Homeland Security. She served as served as an IEEE Distinguished Lecturer between 2002 and 2005. She was also quoted by Silicon India magazine as one of the seven leading technology innovators of South Asian origin in the USA in 2002.
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Using
Semantics to Improve Interactive Information Access
by Lynda Hardman
Centrum Wiskunde & Informatica
Many methods have been developed to extract human-interpretable semantics from signals present in individual media assets. Ensuring that these human-interpretable semantics are also machine processable allows us to identify, describe and connect together fragments of media assets in a rich information environment. Users requiring information are then faced with the problem of finding out what information is available, and obtaining sufficient fragments to successfully carry out their task. Systems supporting these tasks can use the fragments, descriptions of them and relationships among them, to improve both the selection and presentation of information.
This talk will address two issues. Where can semantics play a role in supporting information oriented tasks, and how can they be used to improve support.
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by Lynda Hardman
Centrum Wiskunde & Informatica
Many methods have been developed to extract human-interpretable semantics from signals present in individual media assets. Ensuring that these human-interpretable semantics are also machine processable allows us to identify, describe and connect together fragments of media assets in a rich information environment. Users requiring information are then faced with the problem of finding out what information is available, and obtaining sufficient fragments to successfully carry out their task. Systems supporting these tasks can use the fragments, descriptions of them and relationships among them, to improve both the selection and presentation of information.
This talk will address two issues. Where can semantics play a role in supporting information oriented tasks, and how can they be used to improve support.
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Lynda Hardman
head of the Interactive Information Access group
at Centrum Wiskunde & Informatica
Lynda Hardman (http://www.cwi.nl/~lynda/) is head of the Interactive Information Access group at CWI (Centrum Wiskunde & Informatica) and professor by special appointment of Multimedia Interaction in the Faculty of Science at the University of Amsterdam. She obtained her PhD from the University of Amsterdam in 1998, having graduated in Mathematics and Physics from Glasgow University in 1982. During several years of working in the software industry she was the development manager for Guide - the first hypertext authoring system for personal computers (1986).
Her early experiences in industry with the development of hypertext authoring tools inspired her towards underlying questions of combining time-dependent documents (such as video sequences) along with interaction through links into a single model. She was a member of the W3C working group that developed the first SMIL recommendation.
Since the development of the semantic web, she has dedicated herself to improving human access to the ever-expanding 'linked data cloud'. Her current research efforts are focused on improving design methods for human-based interfaces in relation to developing technology.
She is a member of the editorial board for the Journal of Web Semantics, and the New Review of Hypermedia and Multimedia, and was co-programme chair for SAMT 2008 and ACM Hypertext 2003.
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head of the Interactive Information Access group
at Centrum Wiskunde & Informatica
Lynda Hardman (http://www.cwi.nl/~lynda/) is head of the Interactive Information Access group at CWI (Centrum Wiskunde & Informatica) and professor by special appointment of Multimedia Interaction in the Faculty of Science at the University of Amsterdam. She obtained her PhD from the University of Amsterdam in 1998, having graduated in Mathematics and Physics from Glasgow University in 1982. During several years of working in the software industry she was the development manager for Guide - the first hypertext authoring system for personal computers (1986).
Her early experiences in industry with the development of hypertext authoring tools inspired her towards underlying questions of combining time-dependent documents (such as video sequences) along with interaction through links into a single model. She was a member of the W3C working group that developed the first SMIL recommendation.
Since the development of the semantic web, she has dedicated herself to improving human access to the ever-expanding 'linked data cloud'. Her current research efforts are focused on improving design methods for human-based interfaces in relation to developing technology.
She is a member of the editorial board for the Journal of Web Semantics, and the New Review of Hypermedia and Multimedia, and was co-programme chair for SAMT 2008 and ACM Hypertext 2003.
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Foto Jeroen Oerlemans
Music
Understanding, Music Semantics, and the Future of Music
by Roger B. Dannenberg
School of Computer Science, Art, and Music
Carnegie Mellon University
Music understanding is the automatic recognition of pattern and structure in music. Music understanding problems include matching, searching, and parsing problems related to music recognition and music classification. Music semantics is a more difficult subject. Music, like abstract art, rarely denotes anything specific, and one can argue that music semantics is an oxymoron. Nevertheless, music can be associated with emotions and many other terms or tags, leading to representations similar to those used for semantic computation in other domains. We are at a time of music revolution where old practices of publishing and recording are being challenged by new technologies and consumer expectations. I believe this revolution will continue with the advance of music computation, which will enable new forms of music practice. Music understanding and semantic computing will play an important role in the future of music.
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by Roger B. Dannenberg
School of Computer Science, Art, and Music
Carnegie Mellon University
Music understanding is the automatic recognition of pattern and structure in music. Music understanding problems include matching, searching, and parsing problems related to music recognition and music classification. Music semantics is a more difficult subject. Music, like abstract art, rarely denotes anything specific, and one can argue that music semantics is an oxymoron. Nevertheless, music can be associated with emotions and many other terms or tags, leading to representations similar to those used for semantic computation in other domains. We are at a time of music revolution where old practices of publishing and recording are being challenged by new technologies and consumer expectations. I believe this revolution will continue with the advance of music computation, which will enable new forms of music practice. Music understanding and semantic computing will play an important role in the future of music.
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Manuela Veloso
Herbert A. Simon Professor
Computer Science Department
Carnegie Mellon University
Manuela M. Veloso is Herbert A. Simon Professor of Computer Science at Carnegie Mellon University. She directs the CORAL research laboratory, for the study of agents that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Professor Veloso is a Fellow of the Association for the Advancement of Artificial Intelligence, and the President of the RoboCup Federation. She recently received the 2009 ACM/SIGART Autonomous Agents Research Award for her contributions to agents in uncertain and dynamic environments, including distributed robot localization and world modeling, strategy selection in multiagent systems in the presence of adversaries, and robot learning from demonstration. Professor Veloso is the author of one book on "Planning by Analogical Reasoning" and editor of several other books. She is also an author in over 200 journal articles and conference papers.
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Herbert A. Simon Professor
Computer Science Department
Carnegie Mellon University
Manuela M. Veloso is Herbert A. Simon Professor of Computer Science at Carnegie Mellon University. She directs the CORAL research laboratory, for the study of agents that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Professor Veloso is a Fellow of the Association for the Advancement of Artificial Intelligence, and the President of the RoboCup Federation. She recently received the 2009 ACM/SIGART Autonomous Agents Research Award for her contributions to agents in uncertain and dynamic environments, including distributed robot localization and world modeling, strategy selection in multiagent systems in the presence of adversaries, and robot learning from demonstration. Professor Veloso is the author of one book on "Planning by Analogical Reasoning" and editor of several other books. She is also an author in over 200 journal articles and conference papers.
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Rebecca Crowley
Associate Professor
Biomedical Informatics at the University of Pittsburgh School of Medicine
Director of the Pittsburgh Graduate Training Program in Biomedical Informatics
Rebecca Crowley is an Associate Professor of Biomedical Informatics at the University of Pittsburgh School of Medicine and Director of the Pittsburgh Graduate Training Program in Biomedical Informatics. She received her MD and MS in Information Science from the University of Pittsburgh, and her post-graduate training in Pathology and Neuropathology at Stanford University. Dr. Crowley was a National Library of Medicine (NLM) Fellow in Biomedical Informatics, and a Howard Hughes Medical Institute Fellow in Molecular Neuroendocrinology. Her research interests include applications of semantic technologies to clinical teaching and translational biomedical research as well as the sociotechnical requirements and consequences of sharing biomedical data. Dr. Crowley has also contributed to several large scale biomedical data sharing consortia focused on semantic interoperability including the Cancer Biomedical Informatics Grid (caBIG).
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Associate Professor
Biomedical Informatics at the University of Pittsburgh School of Medicine
Director of the Pittsburgh Graduate Training Program in Biomedical Informatics
Rebecca Crowley is an Associate Professor of Biomedical Informatics at the University of Pittsburgh School of Medicine and Director of the Pittsburgh Graduate Training Program in Biomedical Informatics. She received her MD and MS in Information Science from the University of Pittsburgh, and her post-graduate training in Pathology and Neuropathology at Stanford University. Dr. Crowley was a National Library of Medicine (NLM) Fellow in Biomedical Informatics, and a Howard Hughes Medical Institute Fellow in Molecular Neuroendocrinology. Her research interests include applications of semantic technologies to clinical teaching and translational biomedical research as well as the sociotechnical requirements and consequences of sharing biomedical data. Dr. Crowley has also contributed to several large scale biomedical data sharing consortia focused on semantic interoperability including the Cancer Biomedical Informatics Grid (caBIG).
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Roger B. Dannenberg
Associate Research Professor
School of Computer Science, Art, and Music
Carnegie Mellon University
Dr. Roger B. Dannenberg is an Associate Research Professor in the Schools of Computer Science, Art, and Music at Carnegie Mellon University, where he is also a fellow of the Studio for Creative Inquiry. Dannenberg is well known for his computer music research, especially in real-time interactive systems. His pioneering work in computer accompaniment led to three patents and the SmartMusic system now used by tens of thousands of music students. He also played a central role in the development of the Piano Tutor, an intelligent, interactive, automated multimedia tutor that enables a student to obtain first-year piano proficiency in less than 20 hours. Dannenberg held a patent for large-scale interactive games controlled by crowd noise, and these "stadium games" have entertained many NFL fans. Other innovations include the application of machine learning to music style classification and the automation of music structure analysis. As a trumpet player, he has performed in concert halls ranging from the historic Apollo Theater in Harlem to the Espace de Projection at IRCAM, and he is active in performing jazz, classical, and new works. His compositions have been performed by the Pittsburgh New Music Ensemble, the Pittsburgh Symphony, and at festivals such as the Foro de Musica Nueva, Callejon del Ruido, Spring in Havana, and the International Computer Music Conference.
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Associate Research Professor
School of Computer Science, Art, and Music
Carnegie Mellon University
Dr. Roger B. Dannenberg is an Associate Research Professor in the Schools of Computer Science, Art, and Music at Carnegie Mellon University, where he is also a fellow of the Studio for Creative Inquiry. Dannenberg is well known for his computer music research, especially in real-time interactive systems. His pioneering work in computer accompaniment led to three patents and the SmartMusic system now used by tens of thousands of music students. He also played a central role in the development of the Piano Tutor, an intelligent, interactive, automated multimedia tutor that enables a student to obtain first-year piano proficiency in less than 20 hours. Dannenberg held a patent for large-scale interactive games controlled by crowd noise, and these "stadium games" have entertained many NFL fans. Other innovations include the application of machine learning to music style classification and the automation of music structure analysis. As a trumpet player, he has performed in concert halls ranging from the historic Apollo Theater in Harlem to the Espace de Projection at IRCAM, and he is active in performing jazz, classical, and new works. His compositions have been performed by the Pittsburgh New Music Ensemble, the Pittsburgh Symphony, and at festivals such as the Foro de Musica Nueva, Callejon del Ruido, Spring in Havana, and the International Computer Music Conference.
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Shih-Fu Chang
Professor,
Digital Video and Multimedia Lab
Columbia University
Shih-Fu Chang is Director of Digital Video and Multimedia Lab and Professor and Chairman of Electrical Engineering and at Columbia University. He has also led the ADVENT research consortium at Columbia University with the participation of more than 25 industry sponsors. He has made significant contributions in multimedia search, media forensics, mobile media adaptation, and international standards. He has been recognized with several awards, including IEEE Kiyo Tomiyasu Technical Field Award, IBM Faculty Award, Navy ONR Young Investigator Award, ACM Recognition of Service Award, and NSF CAREER Award. He and his students have received four Best Paper Awards and seven Best Student Paper Awards from IEEE, ACM, and SPIE. Many video indexing technologies developed by his group have been licensed to companies. He was elected to IEEE Fellow in 2004 and was Editor-in-Chief for IEEE Signal Processing Magazine during 2006-8.
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Professor,
Digital Video and Multimedia Lab
Columbia University
Shih-Fu Chang is Director of Digital Video and Multimedia Lab and Professor and Chairman of Electrical Engineering and at Columbia University. He has also led the ADVENT research consortium at Columbia University with the participation of more than 25 industry sponsors. He has made significant contributions in multimedia search, media forensics, mobile media adaptation, and international standards. He has been recognized with several awards, including IEEE Kiyo Tomiyasu Technical Field Award, IBM Faculty Award, Navy ONR Young Investigator Award, ACM Recognition of Service Award, and NSF CAREER Award. He and his students have received four Best Paper Awards and seven Best Student Paper Awards from IEEE, ACM, and SPIE. Many video indexing technologies developed by his group have been licensed to companies. He was elected to IEEE Fellow in 2004 and was Editor-in-Chief for IEEE Signal Processing Magazine during 2006-8.
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Towards
Semantic-Level Visual Search
by Prof. Shih-Fu Chang
Digital Video and Multimedia Lab, Columbia University
With the explosive growth of multimedia content online, researchers have been racing to develop novel solutions for searching images and videos. The Holy Grail has always been a seamless way of accessing multimedia information at the semantic level. However, two major barriers remain in the way – the semantic gap and the intention gap. The former refers to the large difference between machine recognizable information from raw image data and the user desired descriptions at the semantic level. To address this, recently there have been major efforts in developing multimedia ontologies for describing visual concepts, training large resources for automatic concept categorization, and new image search interfaces directly in the visual concept space. The other challenge associated with the intention gap lies in the difficulty in expressing user search targets through the conventional keyword-based methods. In response to this, I will describe two new paradigms. One explores efficient methods (lexical, statistical, and Web) to map keywords to visual detectors and adds real-time interfaces for manipulating queries in the visual concept space. The other completely foregoes the textual query input, instead relies on novel brain machine interfaces and data mining techniques to decode user’s search targets. I will survey on-going research in the above directions aiming towards a semantic-level visual search engine.
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by Prof. Shih-Fu Chang
Digital Video and Multimedia Lab, Columbia University
With the explosive growth of multimedia content online, researchers have been racing to develop novel solutions for searching images and videos. The Holy Grail has always been a seamless way of accessing multimedia information at the semantic level. However, two major barriers remain in the way – the semantic gap and the intention gap. The former refers to the large difference between machine recognizable information from raw image data and the user desired descriptions at the semantic level. To address this, recently there have been major efforts in developing multimedia ontologies for describing visual concepts, training large resources for automatic concept categorization, and new image search interfaces directly in the visual concept space. The other challenge associated with the intention gap lies in the difficulty in expressing user search targets through the conventional keyword-based methods. In response to this, I will describe two new paradigms. One explores efficient methods (lexical, statistical, and Web) to map keywords to visual detectors and adds real-time interfaces for manipulating queries in the visual concept space. The other completely foregoes the textual query input, instead relies on novel brain machine interfaces and data mining techniques to decode user’s search targets. I will survey on-going research in the above directions aiming towards a semantic-level visual search engine.
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Industry Session Call
for Papers
IEEE ICSC 2014: The Eighth IEEE International Conference on Semantic
Computing
September 16-18, 2013
Irvine, CA
Program Goals and Format:
The goals of the ICSC 2014 Industry Session are to foster exchanges
between practitioners and the academics, to promote novel solutions to
today's challenges in the area of Semantic Computing and applications,
to
provide practitioners in the field an early opportunity to evaluate
leading-edge research, and to identify new issues and directions for
future research and development efforts. Similar to regular papers, the
papers in the industry session will undergo a review process and will
appear in the conference proceedings. However, the selection criteria
for
industry papers are slightly different. In particular, papers should
describe technologies, methodologies, applications, prototypes or
experiences of clear industry relevance. A main goal of this session is
to
present research work that exposes the academic and research
communities
to challenges and issues important for the industry. Therefore, the
papers
in this session will be evaluated primarily by the novelty and
applicability of the insights from its industrial solutions, instead of
the originality of its algorithmic content.
Topics of Interest:
Topics of particular interest include but are not limited to those
identified in the main conference CFP, as well as those listed below:
1. Development of new semantic systems, architecture, and standards
2. Employment of semantic computing tools and interfaces
3. Employment of large-scale semantic systems
4. Benchmarking and performance evaluation of semantic systems
5. Innovative solutions for performance optimization
6. Mobile semantic systems and services
7. Multimedia semantic content analysis and retrieval systems
8. Modeling issues and case studies of semantic computing
9. Game and entertainment applications
10. e-Business and other applications
11. Analysis of industry-specific trends and challenges
Important Dates:
Submission: June 10, 2013
Notification: June 28, 2013
Conference: September 16-18, 2013
Industrial Paper Submission:
Industrial papers should be submitted via the ICSC 2014 online paper
submission system. Industry Session papers should be no longer than 8
pages with the same submission guidelines available on the ICSC 2014
web
page. Only electronic submission will be accepted. All industrial
papers
will be peer-reviewed and published in the conference proceedings,
which
will be published by the IEEE Computer Society Press. Submissions must
not
be published or submitted for another conference.
Industry Session Co-Chairs:
Abha Moitra, GE Research, USA
David Ostrowski, Ford, USA
-------------------------------------------------------------
Note:
1. Every paper accepted for publication in the Proceedings of ICSC 2014
MUST be presented during the conference.
2. Every paper accepted for ICSC 2014 MUST have attached to it at least
one registration at the full member/nonmember rate. Thus, for a paper
for
which all authors are students, one student author will be required to
register at the full registration rate.
Program
Committee
S�ren Auer, University of Leipzig, Germany
Agnese Augello, ICAR-CNR
Ramazan Aygun, University of Alabama, Huntsville, USA
Kathy Baker, US Government, USA
Lamberto Ballan, University of Florence, Italy
Roberto Basili, Univ. of Roma Tor Vergata, Italy
Ivan Bedini, Bell Labs
Marco Bertini, Universita' degli Studi di Firenze, Italy
Michael Bloodgood, University of Maryland, USA
David Bracewell, Language Computer Corporation
Volha Bryl, Fondazione Bruno Kessler
Nicoletta Calzolari, Istituto di Linguistica Computazionale del CNR, Italy
Yu Cao, The University of Tennessee at Chattanooga, USA
Kasturi Chatterjee, TechnoratiMedia Inc., USA
Chao Chen, Capital One Bank, USA
Matthew Cooper, FXPAL, USA
Jason Corso, SUNY at Buffalo, USA
Claudia D'Amato, University of Bari, Italy
Ernesto D'Avanzo, Universit� degli Studi di Salerno, Italy
Stamatia Dasiopoulou, Informatics and Telematics Institute, Greece
Thierry Declerck, DFKI GmbH, Germany
Alexiei Dingli, University of Malta
Massimo Esposito,ICAR-CNR, Italy
Alex Chengyu Fang, The City University of Hong Kong, China
Nicola Fanizzi, Dipartimento di Informatica, Universit� di Bari, Italy
Luigi Gallo, ICAR-CNR, Italy
Jose Manuel Gomez-Perez, Intelligent Software Components (iSOCO) S.A.
Thomas Gottron, University of Koblenz-Landau, Germany
William I. Grosky, University of Michigan-Dearborn, USA
Rodrigo Guido, University of Sao Paulo, Brazil
Sanda Harabagiu, University of Texas at Dallas, USA
Choochart Haruechaiyasak, National Electronics and Computer Technology Center, Thailand
Takako Hashimoto, Chiba University of Commerce, Japan
Johannes Heinecke, France Telecom
Ed Hovy, University of Southern California, USA
Zifang Huang, Western Union, USA
Eero Hyv�nen, Aalto University and University of Helsinki, Finland
Maria Jose Ibanez, University of Zaragoza, Spain
Nancy Ide, Vassar College
Hasan Jamil, Wayne State University, USA
Cliff Joslyn, PNNL, USA
Artem Katasonov, VTT Technical Research Centre of Finland, Finland
Lars Knipping, Berlin Institute of Technology, Germany
Shuichi Kurabayashi, Keio University SFC, Japan
Marco La Cascia, University of Palermo, Italy
Freddy Lecue, University of Manchester, UK
Ying Li, IBM T.J. Watson, USA,
Lin Lin, American National Standards Institute, USA
Dianting Liu, University of Miami, USA
Alexander Loui, Eastman Kodak Company, USA,
Hongli Luo, Indiana University - Purdue University Fort Wayne, USA
Mathias Lux, University of Klagenfurt, Austria
Rabi Mahapatra, Texas A&M University, USA
Umberto Maniscalco, CNR, Italy
Elio Masciari, ICAR-CNR, Italy
David Mcdonald, SIFT LLC
Dennis McLeod, University of Southern California, USA
Marge McShane, University of Maryland Baltimore (UMBC), USA
Farid Meziane, University of Salford, UK,
Adrian Mocan, SAP AG, Germany,
Fionn Murtagh, Royal Holloway University of London, UK
Shinichi Nagano, Toshiba Corporation, Japan
Costanza Navarretta, Center for Sprogteknologi,Denmark
Matthias Nickles, Technical University of Munich
Antonio Picariello, Universita` di Napoli "Federico II"
Roberto Pirrone, DINFO - Universita' di Palermo, Italy
Luigi Pontieri, ICAR-CNR, Italy
Sameer Pradhan, BBN Technologies
Alessandro Provetti, University of Messina, Italy
Matthew Purver, Queen Mary University of London, UK
Riccardo Rizzo, ICAR-CNR, Italy
Marco Rospocher, Fondazione Bruno Kessler
Dylan Seychell, University of Malta
Alkis Simitsis, HP Labs
Nadine Steinmetz, Hasso Plattner Institute of Software Systems Engineering, Germany
Heiko Stoermer, University of Trento, Italy
Matthias Thimm, Universit�t Koblenz-Landau, Germany
Marc Tomlinson, Language Computer Corporation
Alfonso Maurizio Urso, ICAR-CNR, Italy
Filippo Vella, ICAR-CNR, Italy
Marc Verhagen, Brandeis University, USA
Ren� Witte, Concordia University, Canada
Jianhua Yan, PayPal, an eBay company, USA
Ziming Zhuang, Yahoo! Labs, USA
S�ren Auer, University of Leipzig, Germany
Agnese Augello, ICAR-CNR
Ramazan Aygun, University of Alabama, Huntsville, USA
Kathy Baker, US Government, USA
Lamberto Ballan, University of Florence, Italy
Roberto Basili, Univ. of Roma Tor Vergata, Italy
Ivan Bedini, Bell Labs
Marco Bertini, Universita' degli Studi di Firenze, Italy
Michael Bloodgood, University of Maryland, USA
David Bracewell, Language Computer Corporation
Volha Bryl, Fondazione Bruno Kessler
Nicoletta Calzolari, Istituto di Linguistica Computazionale del CNR, Italy
Yu Cao, The University of Tennessee at Chattanooga, USA
Kasturi Chatterjee, TechnoratiMedia Inc., USA
Chao Chen, Capital One Bank, USA
Matthew Cooper, FXPAL, USA
Jason Corso, SUNY at Buffalo, USA
Claudia D'Amato, University of Bari, Italy
Ernesto D'Avanzo, Universit� degli Studi di Salerno, Italy
Stamatia Dasiopoulou, Informatics and Telematics Institute, Greece
Thierry Declerck, DFKI GmbH, Germany
Alexiei Dingli, University of Malta
Massimo Esposito,ICAR-CNR, Italy
Alex Chengyu Fang, The City University of Hong Kong, China
Nicola Fanizzi, Dipartimento di Informatica, Universit� di Bari, Italy
Luigi Gallo, ICAR-CNR, Italy
Jose Manuel Gomez-Perez, Intelligent Software Components (iSOCO) S.A.
Thomas Gottron, University of Koblenz-Landau, Germany
William I. Grosky, University of Michigan-Dearborn, USA
Rodrigo Guido, University of Sao Paulo, Brazil
Sanda Harabagiu, University of Texas at Dallas, USA
Choochart Haruechaiyasak, National Electronics and Computer Technology Center, Thailand
Takako Hashimoto, Chiba University of Commerce, Japan
Johannes Heinecke, France Telecom
Ed Hovy, University of Southern California, USA
Zifang Huang, Western Union, USA
Eero Hyv�nen, Aalto University and University of Helsinki, Finland
Maria Jose Ibanez, University of Zaragoza, Spain
Nancy Ide, Vassar College
Hasan Jamil, Wayne State University, USA
Cliff Joslyn, PNNL, USA
Artem Katasonov, VTT Technical Research Centre of Finland, Finland
Lars Knipping, Berlin Institute of Technology, Germany
Shuichi Kurabayashi, Keio University SFC, Japan
Marco La Cascia, University of Palermo, Italy
Freddy Lecue, University of Manchester, UK
Ying Li, IBM T.J. Watson, USA,
Lin Lin, American National Standards Institute, USA
Dianting Liu, University of Miami, USA
Alexander Loui, Eastman Kodak Company, USA,
Hongli Luo, Indiana University - Purdue University Fort Wayne, USA
Mathias Lux, University of Klagenfurt, Austria
Rabi Mahapatra, Texas A&M University, USA
Umberto Maniscalco, CNR, Italy
Elio Masciari, ICAR-CNR, Italy
David Mcdonald, SIFT LLC
Dennis McLeod, University of Southern California, USA
Marge McShane, University of Maryland Baltimore (UMBC), USA
Farid Meziane, University of Salford, UK,
Adrian Mocan, SAP AG, Germany,
Fionn Murtagh, Royal Holloway University of London, UK
Shinichi Nagano, Toshiba Corporation, Japan
Costanza Navarretta, Center for Sprogteknologi,Denmark
Matthias Nickles, Technical University of Munich
Antonio Picariello, Universita` di Napoli "Federico II"
Roberto Pirrone, DINFO - Universita' di Palermo, Italy
Luigi Pontieri, ICAR-CNR, Italy
Sameer Pradhan, BBN Technologies
Alessandro Provetti, University of Messina, Italy
Matthew Purver, Queen Mary University of London, UK
Riccardo Rizzo, ICAR-CNR, Italy
Marco Rospocher, Fondazione Bruno Kessler
Dylan Seychell, University of Malta
Alkis Simitsis, HP Labs
Nadine Steinmetz, Hasso Plattner Institute of Software Systems Engineering, Germany
Heiko Stoermer, University of Trento, Italy
Matthias Thimm, Universit�t Koblenz-Landau, Germany
Marc Tomlinson, Language Computer Corporation
Alfonso Maurizio Urso, ICAR-CNR, Italy
Filippo Vella, ICAR-CNR, Italy
Marc Verhagen, Brandeis University, USA
Ren� Witte, Concordia University, Canada
Jianhua Yan, PayPal, an eBay company, USA
Ziming Zhuang, Yahoo! Labs, USA
The conference group rate for Irvine
Hyatt is $149.00 for single/double with complimentary wireless
internet.
Please make your reservation online HERE.
Please make your reservation online HERE.
Call for Demonstration
IEEE ICSC 2014: The 8th IEEE International Conference on Semantic
Computing
September 16-18, 2013
Irvine, CA
The IEEE ICSC 2014 organizing committee invites proposals for
demonstrations to be given at the conference. The demonstrations
provide a
forum for researchers as well as industry participants to demonstrate
working systems, applications, tools or showcases of base technologies
to
the conference attendees. The goal of the demonstrations is to show a
spectrum ranging from research prototypes to pilots developed and even
products that use semantic technology and provide functionality based
on
semantics in the context of semantic computing. For submissions to this
event, it is very important to describe the demonstration setup,
functionality and benefit to the viewer of the demonstration. Technical
background discussion can be presented at the actual demonstration or
can
be submitted as an industry track or regular conference paper; the
focus
of the demonstration themselves should be to show the functionality to
viewers. It is expected that the demonstrations are highly interactive.
Topics for demonstrations include but are not limited to:
* Content and Information Management
* Knowledge Engineering
* Data Mining
* Semantic Database Theory and Systems
* Service-oriented Architectures and Computing
* Semantic Web and Semantic Web Services
* Multimedia Semantics
* Audio and Speech Processing
* Natural Language Processing
* Semantic Search Technologies and Applications
* User Interfaces
Demonstrations are ideally demonstrating a system or application that
clearly shows the benefit of using and deploying semantics and semantic
technologies. In addition, tools and base technologies that implement
or
use semantic technology or semantic approaches are invited for
demonstration.
Demonstration Setup
The demonstrations are planned to be a single event during a conference
reception function, open to all conference attendees, with the goal of
open and constructive discussions. One table will be provided with
power
as well as an Internet connection. Posters can be put up behind or next
to
the tables (depending on the space) either on pin boards or the wall.
Demonstrators must bring any additional equipment they require as no
equipment will be provided by the conference.
Demonstration Submissions
Authors submitting papers to the demonstrations must submit a 2-page
paper
that clearly outlines the demonstration that will be set up and the
functionality a visitor to the demonstration can observe. The technical
background, such as the architecture or algorithms, should not be
described in detail; such a description would be better submitted to
the
industry track or main conference paper track. Including links to
supporting material, e.g. a video on the web or a web-based demo
itself,
is highly encouraged. All submissions must be in double-column IEEE
format
and follow the specific submission guidelines on the ICSC2012 web page.
The Conference Proceedings will be published by the IEEE Computer
Society
Press and the accepted demonstration submissions will be included in
the
conference proceedings.
Important Dates
Demo Submission: June 10, 2013
Notification: June 28, 2013
Conference: September 16-18, 2013
Submissions
Researchers and practitioners are invited to submit demo proposals to
the
demo co-chair
Please include "[ICSC2013-DEMO]" in the subject of your emails.
Call for Applications
2nd International Summer School on Semantic Computing
July 25-31, 2010
University of California, Berkeley
co-sponsored by IEEE, Institute of Semantic Computing and STI
International
Semantic Computing is currently emerging as a new field that integrates
methods from multimedia (computer vision, speech processing), natural
language processing, semantic web and ontology engineering, software
engineering, and other fields with the goal of creating new
applications that connect intuitively formulated user-intentions with
the content of data.
The summer school will provide an introduction to the field to
senior undergraduate and graduate students. A mix of young and
well-established researchers and educators will present recent research
results, as for example presented in the IEEE conferences on Semantic
Computing. The tutorials will be complemented by keynote talks by
renowned experts in the areas of Semantic Technologies, Ontologies,
Multimedia or Natural Language Processing.
The 6-day event is taking place on the campus of the
University of California, Berkeley and the curriculum will include the
following topics:
- Formal Semantics
- Semantic Web
- Ontology Engineering
- Multimedia
- Natural Language Processing
Important Dates:
* May, 1: Application deadline
* May, 15: Notification of acceptance/Registration opens
* June, 15: Registration completed
* July, 25: School starts
For instruction on how to apply and other information, please
visit the following website: http://sssc2010.org
Technical Paper Preparation Instructions
Manuscripts must be written in English and follow the instructions in the Manuscript Formatting and Templates page
Document templates are located at:
Regular Papers should be no longer than eight (8) pages, Short Papers should be no longer than four (4) pages, Demonstration Papers and Posters should be no longer than two (2) pages.
All paper submissions will be carefully reviewed by at least three experts and reviews will be returned to the author(s) with comments to ensure the high quality of the accepted papers. The authors of accepted papers must guarantee that their paper will be presented at the conference. Please only submit original material where copyright of all parts is owned by the authors declared and which is not currently under review elsewhere. Please see the IEEE policies for further information.
Technical Paper Submission Instructions
Only electronic submission will be accepted. Technical paper authors MUST submit their manuscripts through EasyChair. Please follow this link (please register if not an EasyChair user). Manuscripts may only be submitted in PDF format.
A copyright form needs to be submitted upon acceptance of the paper and is not required at this stage.
Manuscripts must be written in English and follow the instructions in the Manuscript Formatting and Templates page
Document templates are located at:
Regular Papers should be no longer than eight (8) pages, Short Papers should be no longer than four (4) pages, Demonstration Papers and Posters should be no longer than two (2) pages.
All paper submissions will be carefully reviewed by at least three experts and reviews will be returned to the author(s) with comments to ensure the high quality of the accepted papers. The authors of accepted papers must guarantee that their paper will be presented at the conference. Please only submit original material where copyright of all parts is owned by the authors declared and which is not currently under review elsewhere. Please see the IEEE policies for further information.
Technical Paper Submission Instructions
Only electronic submission will be accepted. Technical paper authors MUST submit their manuscripts through EasyChair. Please follow this link (please register if not an EasyChair user). Manuscripts may only be submitted in PDF format.
A copyright form needs to be submitted upon acceptance of the paper and is not required at this stage.
-------------------------------------------------------------
Note:
1. Every paper accepted for publication in the Proceedings of ICSC 2014 MUST be presented during the conference.
2. Every paper accepted for ICSC 2014 MUST have attached to it at least one registration at the full member/nonmember rate. Thus, for a paper for which all authors are students, one student author will be required to register at the full registration rate.
Note:
1. Every paper accepted for publication in the Proceedings of ICSC 2014 MUST be presented during the conference.
2. Every paper accepted for ICSC 2014 MUST have attached to it at least one registration at the full member/nonmember rate. Thus, for a paper for which all authors are students, one student author will be required to register at the full registration rate.
ICSC
Registration Information
The registration deadline is July 21 for authors and July 31 for general participants.
At least one author each paper has to pay a full registration.
We accept online credit card payment. Please access Online Registration System to register.
If you are not in U.S., you might need to ask your credit card bank first to allow foreign transaction.
Email any question regarding registration to Shao-Ting Wang at shaotinw@uci.edu
The registration deadline is July 21 for authors and July 31 for general participants.
At least one author each paper has to pay a full registration.
We accept online credit card payment. Please access Online Registration System to register.
If you are not in U.S., you might need to ask your credit card bank first to allow foreign transaction.
Email any question regarding registration to Shao-Ting Wang at shaotinw@uci.edu
Visa Instructions
Those who need to apply for Visa, please send an email to Dr. George Wang twang@csun.edu as follows:
* In the subject line write "Visa Letter for IEEE ICSC 2014"
* Provide the full title of the paper including the author list and affiliation and the name of the presenter seeking the letter for Visa.
* Indicate the relevant information regarding "Regular", "Short", "Poster", "Industry", etc.
Those who need to apply for Visa, please send an email to Dr. George Wang twang@csun.edu as follows:
* In the subject line write "Visa Letter for IEEE ICSC 2014"
* Provide the full title of the paper including the author list and affiliation and the name of the presenter seeking the letter for Visa.
* Indicate the relevant information regarding "Regular", "Short", "Poster", "Industry", etc.
Author Kit:
ICSC2013 Author Kit Link
Important Date:
ICSC2013 Author Kit Link
Important Date:
- July
21, 2013: Deadline for Camera-ready and Copyright Form
Submissions
Tutorials and Special Workshops
Schedule
1. Monday 9/16 (10:20AM - 12:50PM): Semantic Computing in Financial Industry
2. Monday 9/16 (2PM - 5PM): Semantic Computing in Healthcare Industry
3. Tuesday 9/17 (2PM - 5PM): Semantic Computing for Edutainment
4. Wednesday (2PM - 5PM): Semantic Computing in Social Media
5. Wednesday (7PM - 9:30PM): Human Systems Integration (HSI) in Semantic Computing and Graph Analytics
6. Thursday (9AM - 4PM): Data Science
- Semantic Computing in Financial
Industry (Abstract)
- Semantic Computing in Healthcare
Industry
- Semantic Computing in Social Media
- Semantic Computing for Edutainment
- Data Science
- Human Systems Integration (HSI) in
Semantic Computing
- Graph Analytics
Schedule
1. Monday 9/16 (10:20AM - 12:50PM): Semantic Computing in Financial Industry
2. Monday 9/16 (2PM - 5PM): Semantic Computing in Healthcare Industry
3. Tuesday 9/17 (2PM - 5PM): Semantic Computing for Edutainment
4. Wednesday (2PM - 5PM): Semantic Computing in Social Media
5. Wednesday (7PM - 9:30PM): Human Systems Integration (HSI) in Semantic Computing and Graph Analytics
6. Thursday (9AM - 4PM): Data Science
Conference and Workshop Program
Contacts
Phillip Sheu (psheu@uci.edu): Administrative
Mei-Ling Shyu (shyu@miami.edu): Technical program
George Wang (twang@csun.edu): Local Arrangement
Shao-Ting Wang (shaotinw@uci.edu): Registration
Phillip Sheu (psheu@uci.edu): Administrative
Mei-Ling Shyu (shyu@miami.edu): Technical program
George Wang (twang@csun.edu): Local Arrangement
Shao-Ting Wang (shaotinw@uci.edu): Registration
Coming Soon...
@ IEEE-ICSC 2021