Please use this identifier to cite or link to this item:
Title: Data mining in a large database environment
Authors: Sung, S.Y. 
Wang, K. 
Chua, B.L.
Issue Date: 1996
Citation: Sung, S.Y.,Wang, K.,Chua, B.L. (1996). Data mining in a large database environment. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2 : 988-993. ScholarBank@NUS Repository.
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.
Source Title: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
ISSN: 08843627
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.