標題: Improved negative-border online mining approaches
作者: Wang, CY
Tseng, SS
Hong, TP
資訊工程學系
Department of Computer Science
公開日期: 2006
摘要: In the past, we proposed an extended multidimensional pattern relation (EMPR) to structurally and systematically store previously mining information for each inserted block of data, and designed a negative-border online mining (NOM) approach to provide ad-hoc, query-driven and online mining supports. In this paper, we try to use appropriate data structures and design efficient algorithms to improve the performance of the NOM approach. The lattice data structure is utilized to organize and maintain all candidate itemsets such that the candidate itemsets with the same proper subsets can be considered at the same time. The derived lattice-based NOM (LNOM) approach will require only one scan of the itemsets stored in EMPR, thus saving much computation time. In addition, a hashing technique is used to further improve the performance of the NOM approach since many itemsets stored in EMPR may be useless for calculating the counts of candidates. At last, experimental results show the effect of the improved NOM approaches.
URI: http://hdl.handle.net/11536/12913
ISBN: 3-540-33206-5
ISSN: 0302-9743
期刊: ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
Volume: 3918
起始頁: 483
結束頁: 492
顯示於類別:會議論文