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Our apologizes for
multiple reception. The web site of the workshop has been
updated. ----
CALL FOR PAPERS
MDM/KDD2003 : The Fourth International Workshop on
Multimedia Data Mining
(http://research.it.uts.edu.au/emarkets/mdmkdd2003/ currently updating) in conjunction with
KDD-2003: 9th ACM SIGKDD International Conference
on Knowledge Discovery & Data Mining August 24 - 27, 2003, Washington,
DC, USA (http://www.acm.org/sigkdd/kdd2003/)
(August 24th, 2003) MDM/KDD2003 WORKSHOP THEME : Integrated Media
Mining
THE WORKSHOP The workshop will address issues specifically related to mining information
from multi-modality, multi-source, multi-format data in an integrated way. Many
analysis domains collect data from several sources, including static databases,
streaming data, web pages, or conditionally collected data. Data appear in
multiple forms, including structured, numeric, free text, video, image, speech,
or combinations of several types. Analysis in these domains requires combining
of techniques and integrating methods. Examples include using Text Mining to
generate structured features that can be further used by Data Mining in
conjunction with existing structured data, or combining information mined from a
photo image with text data, meta-data, and web links to other pages.
On the other hand, researchers in multimedia information systems, in the search for techniques for improving the indexing and retrieval of multimedia information are looking into new methods for discovering indexing information. Variety of techniques from machine learning, statistics, databases, knowledge acquisition, data visualization, image analysis, high performance computing, and knowledge-based systems, have been used mainly as a research handcraft activity. The development of multimedia databases and their query interfaces recall again the idea of incorporating multimedia data mining methods for dynamic indexing. The emerging international standard for multimedia content description (MPEG-7) promises to foster the collaboration in the field giving a uniform data representation. The aim of the workshop is to contribute in finding suitable answers to the following questions: - What are the theoretical foundations of multimedia data mining? - What are the problems and applications where multimedia data mining can have severe impact? - What are the advanced architectures of multimedia data mining systems? - What are the specific issues raised in integrated patterns extraction from multimedia data and its components, including images, sound, video, and other non-structured data? - What are suitable multimedia representations and formats that can help data mining in multimedia data? The major topics of the workshop include but are not limited to:
- Integrated mining of different data formats (text, speech, video, structured, image, relational data) - Combining mining results from different sources - Integrated mining methods for eBusiness - Combined mining methods for engineering and manufacturing - Integrated mining for Homeland Security - Mining of data streams combined with structure data - Visual data mining of multi-format/ Multimedia data - Multi-relational Data Mining. The focus is on mining data residing in relational databases. - Visual data mining of multi-format/multimedia data. - Theoretical frameworks for multimedia data mining. - Multimedia data mining methods and algorithms. - Multimedia data sampling and preprocessing. - Data visualization and sonification. - Representation and reuse of discovered knowledge. - Multimedia data descriptions languages and formats. - Evaluation of interestingness, novelty and validity of results. - Topic and event detection in multimedia data (including video). - Extracting semantics from multimedia databases. - Mining scientific multimedia data. - Integrated data mining in multimedia information systems. - Knowledge discovery in facial data. - Man-machine interfaces for multimedia data mining. - Complexity, efficiency and scalability of multimedia data mining algorithms. - Data mining virtual communities and virtual worlds. - Data mining in collaborative virtual environments and virtual reality systems. - Visual and audio support for multimedia mining. - Visual data mining of multimedia data. - Multi-agent environments for concurrent mining of heterogeneous data. - Real-time multimedia data mining systems. - Using MPEG-4 and MPEG-7 standards for multimedia data mining. We encourage submissions of greenhouse work, which present early stages of
a cutting-edge research and development. Software demonstrations are
welcome.
WORKSHOP CO-CHAIRS Valery A. Petrushin,
Accenture Technology Labs161 N. Clark St.Chicago, IL 60089, USA, [EMAIL PROTECTED] WORKSHOP STEERING COMMITTEE Mihael Ankerst,
Boeing, Seattle, USA, [EMAIL PROTECTED] Simeon J. Simoff,
University of Technology, Sydney, Australia, [EMAIL PROTECTED] Chabane Djeraba,
Nantes University, France, [EMAIL PROTECTED] Latifur Khan,
University of Texas at Dallas, USA, [EMAIL PROTECTED] Rod Tjoelker
Boeing, Seattle, USA, [EMAIL PROTECTED] Marko Grobelnik
J. Stefan Institute, Slovenija, [EMAIL PROTECTED] PROGRAM COMMITTEE Dulce Ponceleon
IBM Almaden, USA Wensheng Zhou
Hughes Research Lab, USA Jim Maar
Magnify Research, USA John Risch
Battelle, USA Les Davis
ARDA, USA Dunja Mladenic
J. Stefan Institute, Slovenia Marko Grobelnik
J. Stefan Institute, Slovenia Zhaohui Tang
Microsoft, USA Sundar Venkataraman
Rockwell Scientific Corporation, USA Daniel Barbara
George Mason University, USA Terry Caelli,
University of Alberta, Canada Claude Chrisment
University of Toulouse, France K. Slecuk Candan
Arizona State University, USA Chitra Dorai
IBM Thomas J. Watson Research Center, USA Alex Duffy
University of Strathclyde, UK Max J. Egenhofer
University of Maine, USA Jiawei Han
University of Illinois, USA Howard J. Hamilton
University of Regina, Canada Alexander G. Hauptmann
Carnegie Mellon University, USA Oktay Ibrahimov
Institute of Cybernetics, Azerbaijan Wynne Hsu
National University of Singapore, Singapore Erik Granum
Aalborg University, Denmark William Grosky
University of Michigan,USA Odej Kao
Technical University of Clausthal, Germany Nik Kasabov
University of Ottago, New Zealand Flip Korn
AT&T Laboratories, USA Brian Lovell
University of Queensland, Australia Mike Maybury
MITRE Corporation Dennis McLeod
University of Southern California, USA Monique Noirhomme-Fraiture
Institut Informatique, FUNDP, Belgium Vincent Oria
New Jersey Institute of technology, USA Jian Pei
Simon Fraser University, Canada Cyrus Shahabi
University of Southern California, USA Simone Santini
University of California, San Diego, USA John R. Smith
IBM T. J. Watson Research Center, USA Paul Kennedy
University of Technology-Sydney, Australia Duminda Wijesekera
George Mason University, USA Aidong Zhang
State University of New York at Buffalo, USA SUBMISSION There is no restriction on the length of submissions. Contact author and
email address should be specified. Electronic submission of papers in PDF, PS,
RTF or Microsoft Word Document formats are preferable. The electronic submission
will be organized via e-mail or a conference management system.
DISSEMINATION Peer-reviewed papers, accepted for presentation at the workshop will be
published in the workshop proceedings. Depending on the quality of the papers
and presentations, an edited collection of longer contributions, is planned to
be published either as a special issue of related journal or as an edited
book.
DEADLINES Submissions Due: May 31
Acceptance: June 20 Camera ready copy: July 11 REGISTRATION Registration for the workshop is free for the registrants of KDD-2003.
Workshop attendance is limited to 60 participants only during one
day.
Updated information on the workshop will be available at : http://research.it.uts.edu.au/emarkets/mdmkdd2003/ |
