BEST : an efficient algorithm for mining frequent unordered embedded subtrees


Autoria(s): Chowdhury, Israt Jahan; Nayak, Richi
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

http://eprints.qut.edu.au/78882/

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