Patterns and Logic for Reasoning with Networks

Biomine and ProbLog are two frameworks to implement bisociative information networks (BisoNets). They combine structured data representations with probabilities expressing uncertainty. While Biomine is based on graphs, ProbLog's core language is that of the logic programming language Prolog. This chapter provides an overview of important concepts, terminology, and reasoning tasks addressed in the two systems. It does so in an informal way, focusing on intuition rather than on mathematical definitions. It aims at bridging the gap between network representations and logical ones.

[1]  Luc De Raedt,et al.  Local Query Mining in a Probabilistic Prolog , 2009, IJCAI.

[2]  Paul R. Cohen,et al.  Advances in Intelligent Data Analysis IX, 9th International Symposium, IDA 2010, Tucson, AZ, USA, May 19-21, 2010. Proceedings , 2010, IDA.

[3]  Hannu Toivonen,et al.  Link Discovery in Graphs Derived from Biological Databases , 2006, DILS.

[4]  Joost N. Kok,et al.  Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings , 2007, PKDD.

[5]  Lawrence B. Holder,et al.  Substructure Discovery Using Minimum Description Length and Background Knowledge , 1993, J. Artif. Intell. Res..

[6]  Hannu Toivonen,et al.  Finding reliable subgraphs from large probabilistic graphs , 2008, Data Mining and Knowledge Discovery.

[7]  Petteri Hintsanen The Most Reliable Subgraph Problem , 2007, PKDD.

[8]  Luc De Raedt,et al.  Probabilistic Rule Learning , 2010, ILP.

[9]  Hannu Toivonen,et al.  Finding Representative Nodes in Probabilistic Graphs , 2012, Bisociative Knowledge Discovery.

[10]  Luc De Raedt,et al.  Towards Learning Stochastic Logic Programs from Proof-Banks , 2005, AAAI.

[11]  Joost N. Kok Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings , 2007, ECML.

[12]  Fang Zhou,et al.  A Framework for Path-Oriented Network Simplification , 2010, IDA.

[13]  Luc De Raedt,et al.  Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies) , 2008 .

[14]  Luc De Raedt,et al.  Logical and relational learning , 2008, Cognitive Technologies.

[15]  Luc De Raedt,et al.  On the implementation of the probabilistic logic programming language ProbLog , 2010, Theory and Practice of Logic Programming.

[16]  Hannu Toivonen,et al.  Fast Discovery of Reliable k-terminal Subgraphs , 2010, PAKDD.

[17]  Luc De Raedt,et al.  An Algebraic Prolog for Reasoning about Possible Worlds , 2011, AAAI.

[18]  Stephen Muggleton,et al.  Duce, An Oracle-based Approach to Constructive Induction , 1987, IJCAI.

[19]  Michael R. Berthold Bisociative Knowledge Discovery , 2011, IDA.

[20]  Spyros Tzafestas,et al.  Simply logical: Intelligent reasoning by example , 1995 .

[21]  Tobias Kötter,et al.  From Information Networks to Bisociative Information Networks , 2012, Bisociative Knowledge Discovery.

[22]  Fang Zhou,et al.  Network Simplification with Minimal Loss of Connectivity , 2010, 2010 IEEE International Conference on Data Mining.

[23]  Luc De Raedt,et al.  ProbLog: A Probabilistic Prolog and its Application in Link Discovery , 2007, IJCAI.

[24]  Luc De Raedt,et al.  Probabilistic Explanation Based Learning , 2007, ECML.

[25]  Luc De Raedt,et al.  Compressing probabilistic Prolog programs , 2007, Machine Learning.