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Building a latent semantic index of an image database from patterns of relevance feedback

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1 Author(s)
D. R. Heisterkamp ; Dept. of Comput. Sci., Oklahoma State Univ., Stillwater, OK, USA

This paper proposes a novel view of the information generated by relevance feedback. The latent semantic analysis is adapted to this view to extract useful inter-query information. The view presented in this paper is that the fundamental vocabulary of the system is the images in the database and that relevance feedback is a document whose words are the images. A relevance feedback document contains the intra-query information which expresses the semantic intent of the user over that query. The inter-query information then takes the form of a collection of documents which can be subjected to latent semantic analysis. An algorithm to query the latent semantic index is presented and evaluated against real data sets.

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Pattern Recognition, 2002. Proceedings. 16th International Conference on  (Volume:4 )

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