論文

査読有り
2017年11月15日

Acquisition of Multiple Graph Structured Patterns by an Evolutionary Method Using Sets of TTSP Graph Patterns as Individuals

Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
  • Yuuki Yamagata
  • ,
  • Tetsuhiro Miyahara
  • ,
  • Yusuke Suzuki
  • ,
  • Tomoyuki Uchida
  • ,
  • Fumiya Tokuhara
  • ,
  • Tetsuji Kuboyama

開始ページ
459
終了ページ
464
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/IIAI-AAI.2017.198
出版者・発行元
Institute of Electrical and Electronics Engineers Inc.

Knowledge acquisition from graph structured data is an important task in machine learning and data mining. TTSP (Two-Terminal Series Parallel) graphs are used as data models for electric networks and scheduling. We propose a learning method for acquiring characteristic multiple graph structured patterns by evolutionary computation using sets of TTSP graph patterns as individuals, from positive and negative TTSP graph data, in order to represent sets of TTSP graphs more precisely.

リンク情報
DOI
https://doi.org/10.1109/IIAI-AAI.2017.198
DBLP
https://dblp.uni-trier.de/rec/conf/iiaiaai/YamagataMSUTK17
URL
http://doi.ieeecomputersociety.org/10.1109/IIAI-AAI.2017.198
URL
http://dblp.uni-trier.de/db/conf/iiaiaai/iiaiaai2017.html#conf/iiaiaai/YamagataMSUTK17
ID情報
  • DOI : 10.1109/IIAI-AAI.2017.198
  • DBLP ID : conf/iiaiaai/YamagataMSUTK17
  • SCOPUS ID : 85040559795

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