DocumentCode :
3207649
Title :
MORSA: an algorithm to discover association rules in image data using recurrent items and significant rare items
Author :
Suk, Sang-Kee ; Song, Im-Young ; Kyung-Chang Kim
Author_Institution :
Dept. of Comput. Sci. & Eng., Seoul Nat. Univ. of Technol., South Korea
fYear :
2004
fDate :
8-10 Nov. 2004
Firstpage :
426
Lastpage :
432
Abstract :
Based on preliminary image processing, and content-based image retrieval technology, this paper presents MORSA, an algorithm for discovering association rules among image data using recurrent items and rare items in images stored in image data repository. The rare items to be considered are items that occur infrequently but that take place concurrently with some specific items that happen with frequency above a certain threshold.
Keywords :
content-based retrieval; data mining; image retrieval; multimedia databases; visual databases; MORSA; association rule; content-based image retrieval; image data repository; image database; image processing; recurrent item; significant rare item; Association rules; Computer science; Content based retrieval; Data engineering; Data mining; Frequency; Image processing; Image retrieval; Information retrieval; Multimedia databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Reuse and Integration, 2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN :
0-7803-8819-4
Type :
conf
DOI :
10.1109/IRI.2004.1431498
Filename :
1431498
Link To Document :
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