Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/43567
標題: A data mining approach to database compression
作者: Lee, C.F.
沈肇基
Changchien, S.W.
Wang, W.T.
Shen, J.J.
關鍵字: database compression
data mining
association rules
statistical databases
huffman
algorithm
scheme
sets
期刊/報告no:: Information Systems Frontiers, Volume 8, Issue 3, Page(s) 147-161.
摘要: Data mining can dig out valuable information from databases to assist a business in approaching knowledge discovery and improving business intelligence. Database stores large structured data. The amount of data increases due to the advanced database technology and extensive use of information systems. Despite the price drop of storage devices, it is still important to develop efficient techniques for database compression. This paper develops a database compression method by eliminating redundant data, which often exist in transaction database. The proposed approach uses a data mining structure to extract association rules from a database. Redundant data will then be replaced by means of compression rules. A heuristic method is designed to resolve the conflicts of the compression rules. To prove its efficiency and effectiveness, the proposed approach is compared with two other database compression methods.
URI: http://hdl.handle.net/11455/43567
ISSN: 1387-3326
文章連結: http://dx.doi.org/10.1007/s10796-006-8777-x
Appears in Collections:資訊管理學系

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