CFP - ACM MDM/KDD 2003

Our apologizes for multiple reception. The web site of the workshop has been updated.

 

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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, 
petr@techlabs.accenture.com 

Anne Kao, 
The Boeing Company, P.O. Box 3707 MC 7L-43Seattle, WA 98124-2207, USA, 
anne.kao@boeing.com


WORKSHOP STEERING COMMITTEE

Mihael Ankerst, 
Boeing, Seattle, USA, mihael.ankerst@boeing.com 

Simeon J. Simoff, 
University of Technology, Sydney, Australia, simeon@it.uts.edu.au

Chabane Djeraba, 
Nantes University, France, djeraba@irin.univ-nantes.fr 

Latifur Khan, 
University of Texas at Dallas, USA, lkhan@utdallas.edu

Rod Tjoelker 
Boeing, Seattle, USA, rod.tjoelker@boeing.com 

Marko Grobelnik
J. Stefan Institute, Slovenija, Marko.Grobelnik@ijs.si


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/