Acquisition of Characteristic TTSP Graph Patterns by Genetic Programming

Author

Nagai, Satoshi ; Miyahara, Tetsuhiro ; Suzuki, Yusuke ; Uchida, Tomoyuki

Author_Institution

Grad. Sch. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan

fYear

2012

fDate

20-22 Sept. 2012

Firstpage

340

Lastpage

344

Abstract

Machine learning and data mining from graph structured data are studied intensively. TTSP (Two-Terminal Series Parallel) graphs are used as data models for electric networks and scheduling. A TTSP graph is a directed a cyclic graph obtained by recursively applying "series" and "parallel" operations. We propose an evolutionary method for acquiring characteristic TTSP graph patterns from positive and negative data by using Genetic Programming.

Keywords

data mining; directed graphs; genetic algorithms; learning (artificial intelligence); characteristic TTSP graph patterns; data mining; directed acyclic graph; electric networks; electric scheduling; evolutionary method; genetic programming; graph structured data; machine learning; negative data; positive data; two-terminal series parallel graphs; Data mining; Educational institutions; Evolutionary computation; Genetic programming; Sociology; Statistics; genetic programming; graph mining; machine learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Applied Informatics (IIAIAAI), 2012 IIAI International Conference on

Conference_Location

Fukuoka

Print_ISBN

978-1-4673-2719-0

Type

conf

DOI

10.1109/IIAI-AAI.2012.73

Filename

6337219

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1912444