DocumentCode :
2899114
Title :
Learning semantic cluster for image retrieval using association rule hypergraph partitioning
Author :
Duan, Lijuan ; Chen, Yiqiang ; Gao, Wen
Author_Institution :
Coll. of Comput. Sci., Beijing Univ. of Technol., China
Volume :
3
fYear :
2003
fDate :
15-18 Dec. 2003
Firstpage :
1581
Abstract :
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.
Keywords :
content-based retrieval; image retrieval; learning (artificial intelligence); pattern clustering; relevance feedback; visual databases; association rule hypergraph partitioning; content-based image database management; image extraction; image retrieval; relevance feedback; semantic clustering learning technique; Association rules; Clustering algorithms; Content based retrieval; Feedback; Humans; Image databases; Image retrieval; Information retrieval; Marine vehicles; Partitioning algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
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
Print_ISBN :
0-7803-8185-8
Type :
conf
DOI :
10.1109/ICICS.2003.1292733
Filename :
1292733
Link To Document :
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