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Rüger, Stefan and Magalhaes, Joao
(2005).
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