PROVIDING TIMELY UPDATED SEQUENTIAL PATTERNS IN DECISION MAKING
International Journal of Information Technology & Decision MakingPublished 1 November 2010
Tzung‐Pei Hong, Ching-Yao Wang, Jerry Chun‐Wei Lin
Citations8
SJR quartileQ2
SJR score0.48
SNIP0.80
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TL;DR
A maintenance algorithm for rapidly updating sequential patterns for real-time decision making is proposed that utilizes previously discovered large sequences in the maintenance process, thus greatly reducing the number of database rescans and improving performance.
Abstract
Mining knowledge from large databases has become a critical task for organizations. Managers commonly use the obtained sequential patterns to make decisions. In the past, databases were usually assumed to be static. In real-world applications, however, transactions may be updated. In this paper, a maintenance algorithm for rapidly updating sequential patterns for real-time decision making is proposed. The proposed algorithm utilizes previously discovered large sequences in the maintenance process, thus greatly reducing the number of database rescans and improving performance. Experimental results verify the performance of the proposed approach. The proposed algorithm provides real-time knowledge that can be used for decision making.
Keywords
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