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.

DOI: https://doi.org/10.1145/1076034.1076168

Abstract

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.

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About

• Item ORO ID
• 9089
• 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 or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Depositing User
• Aneta Tumilowicz