DocumentCode :
3250700
Title :
A comparison study on algorithms for incremental update of frequent sequences
Author :
Zhang, Minghua ; Kao, Ben ; Yip, Chi-Lap
Author_Institution :
Dept. of Comput. Sci. & Inf. Syst., Hong Kong Univ., China
fYear :
2002
fDate :
2002
Firstpage :
554
Lastpage :
561
Abstract :
The problem of mining frequent sequences is to extract frequently occurring subsequences in a sequence database. Algorithms on this mining problem include GSP, MFS, and SPADE. The problem of incremental update of frequent sequences is to keep track of the set of frequent sequences as the underlying database changes. Previous studies have extended the traditional algorithms to efficiently solve the update problem. These incremental algorithms include ISM, GSP+ and MFS+. Each incremental algorithm has its own characteristics and they have been studied and evaluated separately under different scenarios. This paper presents a comprehensive study on the relative performance of the incremental algorithms as well as their non-incremental counterparts. Our goal is to provide guidelines on the choice of an algorithm for solving the incremental update problem given the various characteristics of a sequence database.
Keywords :
concurrency control; data mining; database management systems; sequences; GSP; MFS; SPADE; data mining; frequent sequences; incremental algorithm; incremental update; mining frequent sequences; mining problem; relative performance; sequence database; Availability; Computer science; Councils; Data mining; Guidelines; Information systems; Intrusion detection; Itemsets; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7695-1754-4
Type :
conf
DOI :
10.1109/ICDM.2002.1184001
Filename :
1184001
Link To Document :
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