• 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