[3E1-GS-2d] Machine learning

10:15 AM - 10:30 AM JST(1:15 AM - 1:30 AM UTC)

[3E1-GS-2d-06] Acquisition of Multiple Interval Graph Patterns by Evolutionary Learning using Syntactic Similarity based Clustering

Haruki Ikeda⁴, Wataru Komatsu⁴, 〇TETSUHIRO MIYAHARA¹, Tetsuji Kuboyama³, Yusuke Suzuki⁴, Takayoshi Shoudai², Tomoyuki Uchida⁴ (1. Hiroshima City University, Graduate School of Information Sciences, 2. Fukuoka Institute of Technology, 3. Gakushuin University, 4. Hiroshima City University)

Keywords:

evolutionary learning,genetic programming,graph structured pattern

Machine learning and data mining from graph structured data are studied intensively. Using interval representations for allocation of resource and time is useful in problem solving of their overlap and shortage. An interval graph is a graph that represents an interval representation. We propose a method for acquiring characteristic multiple interval graph patterns from positive and negative interval graph data, by evolutionary learning using syntactic similarity based-clustering.