An Exercise in Declarative Modeling for Relational Query Mining

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9575)


Motivated by the declarative modeling paradigm for data mining, we report on our experience in modeling and solving relational query and graph mining problems with the IDP system, a variation on the answer set programming paradigm. Using IDP or other ASP-languages for modeling appears to be natural given that they provide rich logical languages for modeling and solving many search problems and that relational query mining (and ILP) is also based on logic. Nevertheless, our results indicate that second order extensions to these languages are necessary for expressing the model as well as for efficient solving, especially for what concerns subsumption testing. We propose such second order extensions and evaluate their potential effectiveness with a number of experiments in subsumption as well as in query mining.


Knowledge representation Answer set programming Data mining Query mining Pattern mining 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.KU LeuvenHeverleeBelgium

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