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
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;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.151