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Polynomial Time Inductive Inference of Cograph Pattern Languages from Positive Data

  • Yuta Yoshimura
  • Takayoshi Shoudai
  • Yusuke Suzuki
  • Tomoyuki Uchida
  • Tetsuhiro Miyahara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7207)

Abstract

A cograph (complement reducible graph) is a graph which can be generated by disjoint union and complement operations on graphs, starting with a single vertex graph. Cographs arise in many areas of computer science and are studied extensively.

With the goal of developing an effective data mining method for graph structured data, in this paper we introduce a graph pattern expression, called a cograph pattern, which is a special type of cograph having structured variables. Firstly, we present a polynomial time matching algorithm for cograph patterns. Secondly, we give a polynomial time algorithm for obtaining a minimally generalized cograph pattern which explains given positive data. Finally, we show that the class of cograph pattern languages is polynomial time inductively inferable from positive data.

Keywords

Polynomial Time Disjoint Union Internal Node Polynomial Time Algorithm Graph Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuta Yoshimura
    • 1
  • Takayoshi Shoudai
    • 1
  • Yusuke Suzuki
    • 2
  • Tomoyuki Uchida
    • 2
  • Tetsuhiro Miyahara
    • 2
  1. 1.Department of InformaticsKyushu UniversityJapan
  2. 2.Department of Intelligent SystemsHiroshima City UniversityJapan

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