DocumentCode
3509731
Title
Hardness of Learning Unordered Tree Contraction Patterns
Author
Okamoto, Yuji ; Shoudai, Takayoshi
Author_Institution
Dept. of Inf., Kyushu Univ., Fukuoka, Japan
fYear
2013
fDate
Aug. 31 2013-Sept. 4 2013
Firstpage
141
Lastpage
146
Abstract
A tree contraction pattern (TC-pattern) is an unordered tree-structured pattern common to given unordered trees, which is obtained by merging every uncommon connected substructure into one vertex by edge contraction. In order to extract meaningful and hidden knowledge from tree structured documents, we consider a minimal language (MINL) problem for TC-patterns. The MINL problem for TC-patterns is to find one of the minimally generalized TC-pattern that are matched by all given unordered trees. Recently, Yoshimura and Shoudai (2013) showed that the MINL problem for the class of TC-patterns with a constant parameter is computable in polynomial time. In this paper, we discuss two optimization versions of the MINL problem, and show that the two problems are NP-complete.
Keywords
computational complexity; computational linguistics; document handling; learning (artificial intelligence); tree data structures; MINL problem; NP-complete problem; TC-pattern; edge contraction; minimal language problem; tree structured documents; unordered tree contraction pattern learning; unordered tree-structured pattern; Informatics; Merging; Minimization; Optimization; Pattern matching; Polynomials; Transforms; Web mining; computational complexity; learning theory; minimal language problem; tree-structured pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Applied Informatics (IIAIAAI), 2013 IIAI International Conference on
Conference_Location
Los Alamitos, CA
Print_ISBN
978-1-4799-2134-8
Type
conf
DOI
10.1109/IIAI-AAI.2013.63
Filename
6630334
Link To Document