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Mining multimedia salient concepts for incremental information extraction

Rüger, Stefan and Magalhaes, Joao (2005). Mining multimedia salient concepts for incremental information extraction. In: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '05), 15-19 Aug 2005, Salvador, Brazil.

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We propose a novel algorithm for extracting information by mining the feature space clusters and then assigning salient concepts to them. Bayesian techniques for extracting concepts from multimedia usually suffer either from lack of data or from too complex concepts to be represented by a single statistical model. An incremental information extraction approach, working at different levels of abstraction, would be able to handle concepts of varying complexities. We present the results of our research on the initial part of an incremental approach, the extraction of the most salient concepts from multimedia information.

Item Type: Conference or Workshop Item
Extra Information: ISBN of published proceedings: 1-59593-034-5
pages 641-642
Keywords: multimedia clustering; multimedia information extraction
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 9089
Depositing User: Aneta Tumilowicz
Date Deposited: 05 Oct 2007
Last Modified: 12 Jun 2020 09:18
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