BOSTER : an efficient algorithm for mining frequent unordered induced subtrees
Chowdhury, Israt J. & Nayak, Richi (2014) BOSTER : an efficient algorithm for mining frequent unordered induced subtrees. Lecture Notes in Computer Science : Web Information Systems Engineering – WISE 2014, 8786, pp. 146-155.
Extracting frequent subtrees from the tree structured data has important applications in Web mining. In this paper, we introduce a novel canonical form for rooted labelled unordered trees called the balanced-optimal-search canonical form (BOCF) that can handle the isomorphism problem efficiently. Using BOCF, we define a tree structure guided scheme based enumeration approach that systematically enumerates only the valid subtrees. Finally, we present the balanced optimal search tree miner (BOSTER) algorithm based on BOCF and the proposed enumeration approach, for finding frequent induced subtrees from a database of labelled rooted unordered trees. Experiments on the real datasets compare the efficiency of BOSTER over the two state-of-the-art algorithms for mining induced unordered subtrees, HybridTreeMiner and UNI3. The results are encouraging.
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|Item Type:||Journal Article|
|Additional Information:||15th International Conference, Thessaloniki, Greece, October 12-14, 2014, Proceedings, Part I|
|Keywords:||Web mining, Frequent subtrees, Labelled rooted unordered trees, Induced subtrees, Canonical form, Enumeration approach|
|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/10.1007/978-3-319-11749-2_12|
|Deposited On:||24 Nov 2014 00:01|
|Last Modified:||29 Nov 2014 03:57|
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