DocumentCode :
2499021
Title :
Data mining in a large database environment
Author :
Sung, S.Y. ; Wang, K. ; Chua, B.L.
Author_Institution :
Dept. of Inf. Syst. & Comput. Sci., Nat. Univ. of Singapore, Singapore
Volume :
2
fYear :
1996
fDate :
14-17 Oct 1996
Firstpage :
988
Abstract :
Data mining, the process of discovering hidden and potentially useful information from very large databases, has been recognized as one of the most promising research topics in the 1990s. The essential problem faced in the mining of association rules is the generation of large items, which are items that are present in at least s% (minimal support) of the total database tuples. As the large items and their counts information usually require much storage space, the minimal cover concept is introduced to achieve reductions in the storage size. Percentage contour, an extension of minimal cover, is further introduced to aid in the handling of large databases
Keywords :
deductive databases; knowledge acquisition; very large databases; association rules; data mining; database tuples; minimal cover; percentage contour; very large databases; Association rules; Computer science; Dairy products; Data analysis; Data mining; Electronic mail; Information systems; Machine learning; Marketing and sales; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1062-922X
Print_ISBN :
0-7803-3280-6
Type :
conf
DOI :
10.1109/ICSMC.1996.571213
Filename :
571213
Link To Document :
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