Inferring the Structure of Graph Grammars from Data
作者： Fang Huang , Shailesh P. Doshi
DOI:
关键词: Voltage graph 、 Power graph analysis 、 Graph property 、 Graph database 、 Mathematics 、 Graph rewriting 、 Theoretical computer science 、 Directed graph 、 Null graph 、 Clique-width
摘要: Graphs can be used to represent such diverse entities as chemical compounds, transportation networks, and the world wide web. Stochastic graph grammars are compact representations of probability distributions over graphs. We present an algorithm for inferring stochastic from data. That is, given a set graphs that, example, correspond all which have some desirable property, uncovers structure shared by represents it in form grammar. The inferred grammar assigns high was learned low other report results preliminary experiments compared target generated training
umbc.edu参考文章(11)
Bill Keller, Rüdi Lutz, Evolving stochastic context-free grammars from examples using a minimum description length principle ,(1997)
Matthieu Latapy, Jean-Loup Guillaume, The Web Graph: an Overview Actes d'ALGOTEL'02 (Quatrièmes Rencontres Francophones sur les aspects Algorithmiques des Télécommunications). ,(2002)
Luc Dehaspe, Hannu Toivonen, Ross Donald King, Finding frequent substructures in chemical compounds knowledge discovery and data mining. pp. 30- 36 ,(1998)
Lawrence B. Holder, Diane J. Cook, Jesus A. Gonzalez, Graph-Based Concept Learning the florida ai research society. pp. 377- 381 ,(2001)
Andreas Stolcke, Bayesian learning of probabilistic language models University of California at Berkeley. ,(1994)
Mohamed Mosbah, Probabilistic Graph Grammars workshop on graph theoretic concepts in computer science. pp. 236- 247 ,(1992) , 10.1007/3-540-56402-0_51
Mark Derthick, A minimal encoding approach to feature discovery national conference on artificial intelligence. pp. 565- 571 ,(1991)
M.W. Craven, J.W. Shavlik, Machine learning approaches to gene recognition IEEE Intelligent Systems. ,vol. 9, pp. 2- 10 ,(1994) , 10.1109/64.294127
Ken'ichi Yoshida, Hiroshi Motoda, CLIP: concept learning from inference patterns Artificial Intelligence. ,vol. 75, pp. 63- 92 ,(1995) , 10.1016/0004-3702(94)00066-A
D.J. Cook, L.B. Holder, Graph-based data mining IEEE Intelligent Systems & Their Applications. ,vol. 15, pp. 32- 41 ,(2000) , 10.1109/5254.850825