OCTOPUS: aggressive search of multi-modality data using multifaceted knowledge base
Proceedings of the 11th international conference on World Wide Web
Personal media data organization and retrieval in e-learning: a collaborative tagging based approach
MTDL '09 Proceedings of the first ACM international workshop on Multimedia technologies for distance learning
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PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
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The major challenges of multimedia retrieval are the difficulty of generating semantic indexes, as well as the incapability of identifying personalized user interests. This paper attempts to address both problems by suggesting a collaborative yet personalized approach for web-based multimedia retrieval, which employs a synergy between relevance feedback technique from the Information Retrieval community, and user profiling technique from the Information Filtering community. Specifically, a "common profile" is established to represent the common knowledge on the semantics of multimedia data, which allow a user to "learn from others" in the retrieval process. On the other hand, for each user a "user profile" is constructed to characterize his/her personal views, which allow a user to "learn from own history". Both types of profiles can be learned and updated incrementally from user feedbacks. By using an integrated retrieval algorithm based on profiles, this approach strikes the balance between exploiting the common knowledge of most users and catering for the personalized interest of a particular user. The results of some preliminary experiments have demonstrated the effectiveness of the proposed approach.