Multimedia information is ubiquitous and essential in many applications from homeland security to medicine and bioinformatics. As evidenced by the success of the previous editions of MDM/KDD, there is an increasing need in new techniques and tools that can detect and discover patterns, in multimedia data, that can lead to new knowledge. For example, tools are needed for discovering relationships between objects or segments within images, classifying images based on their content, extracting patterns in sound, categorizing speech and music, and recognizing and tracking objects in video streams. There is also an increasing interest in the real-time analysis of multimedia data generated by distributed sensory applications and ambient intelligence environments.

MDM is a leading venue where researchers, both from the academia and industry, can exchange and compare both relatively mature and green house theories, methodologies, algorithms and frameworks for multimedia data mining. To address this aim, the workshop brings together experts in the analysis of digital media content, multimedia databases, multimedia information retrieval, and domain experts from different applied disciplines with potential in multimedia data mining and knowledge discovery. The previous seven workshops have been held in conjunction with KDD 2000 (Boston, MA), KDD2001 (San Francisco, CA), KDD 2002 (Edmonton, Canada), KDD 2003 (Washington, DC), KDD 2004 (Seattle, WA), KDD 2005 (Chicago, IL), and KDD 2006 (Philadelphia, PA) respectively.

Like the previous editions, MDM 2007 will aim facilitating cross-disciplinary exchange of ideas. The major topics of the workshop include but are not limited to:

• Integrated mining of different data formats (text, speech, video, images, relational data)
• Combining mining results from different sources
• Mining of data streams combined with structure data
• Mining of multi-format/multimedia/multi-modal data
• Theoretical frameworks for multimedia data mining.
• Multimedia data sampling and preprocessing.
• Representation and reuse of discovered knowledge.
• Multimedia data description languages and formats.
• Topic and event detection in multimedia data
• Extracting semantics from multimedia databases.
• Mining scientific multimedia data.
• Man-machine interfaces for multimedia data mining.
• Complexity, efficiency and scalability of multimedia data mining algorithms.
• Data mining virtual communities and virtual worlds.
• Real-time multimedia data mining systems.

Papers, accepted for presentation at the workshop will be published in the workshop proceedings. All submitted papers will be refereed for quality and originality by the Program Committee. The acceptance/rejection of the papers will be based on these review results. Manuscripts should be in English and must not exceed 10 pages (ACM format). Submissions should include the title, author(s), authors' affiliations, e-mail addresses, tel/fax numbers, postal address, and an abstract on the first page. An electronic version (PDF format) of the full paper should be submitted by May 11th, 2007 by email to candan@asu.edu. For further information please contact the MDM'07 co-chairs:

K. Selcuk Candan
Dept. of Computer Science and Engineering
Arizona State University
Tempe, AZ 85287-8809, USA
phone: (480) 965-2770
fax: (480) 965-2751
email: candan@asu.edu
http://www.public.asu.edu/~candan

Zhongfei (Mark) Zhang
Computer Science Department
Watson School, SUNY Binghamton
Binghamton, NY 13902-6000, USA
email:zhongfei@cs.binghamton.edu
http://www.cs.binghamton.edu/~zhongfei/