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.
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.