BEST : an efficient algorithm for mining frequent unordered embedded subtrees
Contribuinte(s) |
Pham, Duc Nghia Park, Seong-Bae |
---|---|
Data(s) |
2014
|
Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Publicador |
Springer International Publishing |
Relação |
http://eprints.qut.edu.au/78882/4/78882.pdf DOI:10.1007/978-3-319-13560-1_37 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. |
Direitos |
Copyright 2014 Springer International Publishing Switzerland The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-13560-1_37 |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #080000 INFORMATION AND COMPUTING SCIENCES #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #080109 Pattern Recognition and Data Mining #anzsrc Australian and New Zealand Standard Research Class #Frequent subtrees #Labelled rooted unordered trees #Embedded subtrees #Canonical form #Enumeration approach |
Tipo |
Journal Article |