The increasing application of collaborative computing and multimedia document handling in the majority of government, business and educational intra- and internets provides enormous sources of various data, organised in different structures and formats. No wonder researchers in multimedia turned towards the field of data mining and knowledge discovery in databases in the search for techniques for improving the indexing and retrieval of multimedia information. In the beginning, a variety of techniques from machine discovery, statistics, databases, knowledge acquisition, machine learning, 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 data mining methods for dynamic indexing. Recently data mining efforts have focused in less formalised fields of art, design, hypermedia information systems, case-based reasoning and computational modeling of creativity. These and similar fields use variety of data sources, incorporated through sophisticated digital media data structures. As a result there is an urgent need for new techniques and tools that can transform these rich data into useful information and knowledge.

The aim of this workshop is to bring together experts in analysis of digital media content, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from different applied disciplines with potential in multimedia data mining. The major topics of the workshop include but are not limited to:

• multimedia data mining methods and algorithms;
• knowledge discovery and knowledge extraction from image data;
• knowledge discovery and knowledge extraction from sound data;
• knowledge discovery and knowledge extraction from video data;
• automatic video annotation and indexing;
• real-time object detection in video streams;
• electronic documents - multimedia data representation and reuse of discovered knowledge;
• content-based search, retrieval, and discovery methods;
• uncertainty management in multimedia data mining;
• complexity, efficiency and scalability of multimedia data mining algorithms;
• the incorporation of domain knowledge;
• multimedia data mining and interactive exploration;
• multimedia data visualization and man-machine interfaces;
• integrated data mining of text and image data;
• data analysis of video and audio data;
• representation of discovered knowledge
• active storage for data mining in multimedia;
• mining from unstructured and semi-structured data;
• web-content mining;
• data mining from XML documents;
• mining from Geographic Information Systems.
• data mining in collaborative virtual environments and virtual reality systems.

Please, e-mail electronic submissions with subject "MDM/KDD2001" to:

mdm-chairs@cs.ualberta.ca