Rüger, Stefan and Magalhaes, Joao
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|DOI (Digital Object Identifier) Link:||http://doi.org/10.1145/1076034.1076168|
|Google Scholar:||Look up in Google Scholar|
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 Item|
|Extra Information:||ISBN of published proceedings: 1-59593-034-5
|Keywords:||multimedia clustering; multimedia information extraction|
|Academic Unit/Department:||Knowledge Media Institute|
|Depositing User:||Aneta Tumilowicz|
|Date Deposited:||05 Oct 2007|
|Last Modified:||23 Mar 2016 08:11|
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