DocumentCode
2142716
Title
Incrementally Mining High Utility Itemsets in Dynamic Databases
Author
Lin, Chun-Wei ; Hong, Tzung-Pei ; Lan, Guo-Cheng ; Chen, Hsin-Yi ; Kao, Hung-Yu
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear
2010
fDate
14-16 Aug. 2010
Firstpage
303
Lastpage
307
Abstract
Utility mining is proposed to consider additional measures, such as profits or costs according to user preference. In the past, a two-phase mining algorithm was proposed for fast discovering high utility itemsets from databases. In this paper, an incremental mining algorithm to efficiently update high utility itemsets is proposed for record insertion. Experimental results also show that the proposed algorithm executes faster than the two-phase batch mining algorithm.
Keywords
data mining; database management systems; dynamic databases; incremental mining; two-phase batch mining algorithm; user preference; utility itemsets; Algorithm design and analysis; Association rules; Computer science; Conferences; Itemsets;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location
San Jose, CA
Print_ISBN
978-1-4244-7964-1
Type
conf
DOI
10.1109/GrC.2010.151
Filename
5575938
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