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Focus

So far, several approaches have been developed that tackle specific problems of the retrieval process, e.g. feature extraction methods for multimedia data, query languages, problem-specific similarity measures and interactive user interfaces. However, in most cases the user still needs several steps in order to find the searched objects. The main reasons for this are on the one hand, the users' difficulty in specifying their interests in the form of a well-defined query, on the other hand, the problem of extracting relevant (semantic) features from the multimedia objects. Furthermore, user specific interests and the search context are usually neglected when objects are retrieved.

To improve today's retrieval tools and thus the overall satisfaction of a user, it is necessary to develop intelligent methods that are able to support the user in the search process, e.g. by providing additional user adapted information about the search results as well as the data collection itself and especially by adapting the retrieval tool to the user's needs and interests.

The goal of this workshop is therefore to intensify the exchange of ideas between different research communities, to provide an overview of current activities in this area and to point out connections between the diverse involved research communities: multimedie retrieval and artificial intelligence.

The workshop focuses especially on researchers that are working on feature extraction techniques for multimedia, computer linguistic approaches, (dynamic) data analysis methods, interactive machine learning and visualisation methods as well as user interface design. Therefore, contributions to the workshop should focus on, but are not limited to:

• Multimedia retrieval systems (for text, image, audio, video and mixed-media)
• Theoretical foundations of multimedia retrieval and mining
• Intelligent multimedia data modelling, indexing and structure extraction
• Adaptive Hypermedia and web based systems
• Metadata for multimedia retrieval
• Multimedia and multi-modal mining
• Semantic content analysis for multimedia
• Semantic web and ontologies
• Adaptive query languages
• Similarity measures (especially user adaptive measures)
• User and preference modelling (including feedback models)
• Methods for adaptive data visualisation and user interfaces