A Low-Scan Incremental Association Rule Maintenance Method Based on the Apriori Property
Document Type
Conference Paper
Publication Date
6-7-2001
Publication Title
Conference of the Canadian Society for Computational Studies of Intelligence
First Page
26
Last Page
35
Abstract
As new transactions update data sources and subsequently the data warehouse, the previously discovered association rules in the old database may no longer be interesting rules in the new database. Furthermore, some new interesting rules may appear in the new database. This paper presents a new algorithm for efficiently maintaining discovered association rules in the updated database, which starts by computing the high n level large itemsets in the new database using the available high n level large itemsets in the old database. Some parts of the n-1; n-2,...,1 level large itemsets can then be quickly generated by applying the apriori property, thereby avoiding the overhead of calculating many lower level large itemsets that involve huge table scans.
DOI
10.1007/3-540-45153-6_3
Recommended Citation
Zhou, Z.. (2001). A Low-Scan Incremental Association Rule Maintenance Method Based on the Apriori Property. Conference of the Canadian Society for Computational Studies of Intelligence, 26-35.
https://scholar.uwindsor.ca/computersciencepub/20