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 :
بازگشت