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Title: Dynamic itemset mining under multiple support thresholds
Authors: Abuzayed, Nourhan
Ergenç, Belgin
Keywords: Association rule mining
Itemset mining
Dynamic itemset mining
Multiple support thresholds
Publisher: IOS Press
Series/Report no.: Frontiers in Artificial Intelligence and Applications
Abstract: Handling dynamic aspect of databases and multiple support threshold requirements of items are two important challenges of frequent itemset mining algorithms. Existing dynamic itemset mining algorithms are devised for single support threshold whereas multiple support threshold algorithms assume that the databases are static. This paper focuses on dynamic update problem of frequent itemsets under MIS (Multiple Item Support) thresholds and introduces Dynamic MIS algorithm. It is i) tree based and scans the database once, ii) considers multiple support thresholds, and iii) handles increments of additions, additions with new items and deletions. Proposed algorithm is compared to CFP-Growth++ and findings are; in dynamic database 1) Dynamic MIS performs better than CFP-Growth++ since it runs only on increments and 2) Dynamic MIS can achieve speed-up up to 56 times against CFP-Growth++.
Description: 2nd International Conference on Fuzzy Systems and Data Mining (FSDM) -- DEC 11-14, 2016 -- Macau
ISBN: 978-1-61499-722-1
ISSN: 0922-6389
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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