Compressing probabilistic Prolog programs

被引:19
|
作者
De Raedt, L. [1 ]
Kersting, K. [2 ]
Kimmig, A. [1 ]
Revoredo, K. [2 ]
Toivonen, H. [3 ]
机构
[1] Katholieke Univ Leuven, Dept Computerwetenschappen, B-3001 Heverlee, Belgium
[2] Univ Freiburg, Inst Informat, D-79100 Freiburg, Germany
[3] Univ Helsinki, Dept Comp Sci, FIN-00014 Helsinki, Finland
关键词
probabilistic logic; inductive logic programming; theory revision; compression; network mining; biological applications; statistical relational learning;
D O I
10.1007/s10994-007-5030-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
ProbLog is a recently introduced probabilistic extension of Prolog (De Raedt, et al. in Proceedings of the 20th international joint conference on artificial intelligence, pp. 2468-2473, 2007). A ProbLog program defines a distribution over logic programs by specifying for each clause the probability that it belongs to a randomly sampled program, and these probabilities are mutually independent. The semantics of ProbLog is then defined by the success probability of a query in a randomly sampled program. This paper introduces the theory compression task for ProbLog, which consists of selecting that subset of clauses of a given ProbLog program that maximizes the likelihood w.r.t. a set of positive and negative examples. Experiments in the context of discovering links in real biological networks demonstrate the practical applicability of the approach.
引用
收藏
页码:151 / 168
页数:18
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