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Learning semantic cluster for image retrieval using association rule hypergraph partitioning

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3 Author(s)
Lijuan Duan ; Coll. of Comput. Sci., Beijing Univ. of Technol., China ; Yiqiang Chen ; Wen Gao

Semantic clustering is an important and challenging task for content-based image database management. This paper proposes a semantic clustering learning technique, which collects the relevance feedback image retrieval transaction and uses hypergraph to represent images correlation ship, then obtains the semantic clusters by hypergraph partitioning. Experiments show that it is efficient and simple.

Published in:

Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on  (Volume:3 )

Date of Conference:

15-18 Dec. 2003