DocumentCode :
2796454
Title :
Incrementally fast updated sequential pattern trees
Author :
Hong, Tzung-Pei ; Chen, Hsin-Yi ; Lin, Chun-Wei ; Li, Sheng-Tun
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung
Volume :
7
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
3991
Lastpage :
3996
Abstract :
In the past, the FUFP-tree maintenance algorithm is proposed to efficiently handle the association rules in incremental mining. In this paper, we attempt to modify the FUFP-tree maintenance algorithm for maintaining sequential patterns based on the concept of pre-large sequences to reduce the need for rescanning original databases in incremental mining. A fast updated sequential pattern trees (FUSP trees) structure and the maintenance algorithm are proposed, which makes the tree update process become easier. It does not require rescanning original customer sequences until the accumulative amount of newly added customer sequences exceed a safety bound, which depends on database size. The proposed approach thus becomes efficiently and effectively for handling newly added customer sequences.
Keywords :
data mining; tree data structures; FUSP-tree maintenance algorithm; association rules; fast updated frequent pattern tree; fast updated sequential pattern trees; incremental mining; Association rules; Computer science; Cybernetics; Data mining; Electronic mail; Information management; Machine learning; Machine learning algorithms; Transaction databases; Tree data structures; Data mining; FUSP tree; incremental mining; large sequence; pre-large sequence; sequential pattern;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4621100
Filename :
4621100
Link To Document :
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