[2I1-GS-3] Knowledge utilization and sharing:

[2I1-GS-3-01] Acquisition of Characteristic Interval Graph Patterns using Evolutionary Learning

Shuichiro Yamamoto¹, Wataru Komatsu¹, 〇Tetsuhiro Miyahara¹, Yusuke Suzuki¹, Takayoshi Shoudai², Tomoyuki Uchida¹, Tetsuji Kuboyama³ (1. Hiroshima City University, 2. Fukuoka Institute of Technology, 3. Gakushuin 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 interval graph patterns from positive and negative interval graph data, by using evolutionary learning.