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
Link To Document :
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