IMPROVING EFFICIENCY OF INCREMENTAL MINING BY TRIE STRUCTURE AND PRE-LARGE ITEMSETS

Title
IMPROVING EFFICIENCY OF INCREMENTAL MINING BY TRIE STRUCTURE AND PRE-LARGE ITEMSETS
Author(s)
황도삼Thien-Phuong LE[Thien-Phuong LE]Bay Vo[Bay Vo]Bac LE[Bac LE]Tzung-Pei Hong[Tzung-Pei Hong]
Keywords
FREQUENT PATTERN TREES; SEQUENTIAL PATTERNS; PERSPECTIVE; ALGORITHM
Issue Date
201409
Publisher
SLOVAK ACAD SCIENCES INST INFORMATICS
Citation
COMPUTING AND INFORMATICS, v.33, no.3, pp.609 - 632
Abstract
Incremental data mining has been discussed widely in recent years, as it has many practical applications, and various incremental mining algorithms have been proposed. Hong et al. proposed an efficient incremental mining algorithm for handling newly inserted transactions by using the concept of pre-large itemsets. The algorithm aimed to reduce the need to rescan the original database and also cut maintenance costs. Recently, Lin et al. proposed the Pre-FUFP algorithm to handle new transactions more efficiently, and make it easier to Update the FP-tree. However, frequent itemsets must be mined from the FP-growth algorithm. In this paper, we propose a Pre-FUT algorithm (Fast-Update algorithm using the Trie data structure and the concept of pre-large itemsets), which not only builds and updates the trie structure when new transactions are inserted, but also mines all the frequent itemsets easily from the tree. Experimental results show the good performance of the proposed algorithm.
URI
http://hdl.handle.net/YU.REPOSITORY/30795
ISSN
1335-9150
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
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