BEST : an efficient algorithm for mining frequent unordered embedded subtrees

Chowdhury, Israt Jahan & Nayak, Richi (2014) BEST : an efficient algorithm for mining frequent unordered embedded subtrees. Lecture Notes in Computer Science : PRICAI 2014: Trends in Artificial Intelligence, 8862, pp. 459-471.

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Abstract

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.

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ID Code: 78882
Item Type: Journal Article
Refereed: Yes
Additional Information: 13th Pacific Rim International Conference on Artificial Intelligence, Gold Coast, QLD, Australia, December 1-5, 2014. Proceedings
Keywords: Frequent subtrees, Labelled rooted unordered trees, Embedded subtrees, Canonical form, Enumeration approach
DOI: 10.1007/978-3-319-13560-1_37
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Springer International Publishing Switzerland
Copyright Statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-13560-1_37
Deposited On: 23 Nov 2014 23:55
Last Modified: 08 Dec 2014 03:53

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