Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3. Blockeel, H., Bogaerts, B., Bruynooghe, M., De Cat, B., De Pooter, S., Denecker, M., Jansen, J., Labarre, A., Ramon, J., & Verwer, S. *Theory and Practice of Logic Programming*, 15(6):783--817, November, 2015.

Paper Arxiv doi abstract bibtex

Paper Arxiv doi abstract bibtex

This paper provides a gentle introduction to problem solving with the IDP3 system. The core of IDP3 is a finite model generator that supports first order logic enriched with types, inductive definitions, aggregates and partial functions. It offers its users a modeling language that is a slight extension of predicate logic and allows them to solve a wide range of search problems. Apart from a small introductory example, applications are selected from problems that arose within machine learning and data mining research. These research areas have recently shown a strong interest in declarative modeling and constraint solving as opposed to algorithmic approaches. The paper illustrates that the IDP3 system can be a valuable tool for researchers with such an interest. The first problem is in the domain of stemmatology, a domain of philology concerned with the relationship between surviving variant versions of text. The second problem is about a somewhat related problem within biology where phylogenetic trees are used to represent the evolution of species. The third and final problem concerns the classical problem of learning a minimal automaton consistent with a given set of strings. For this last problem, we show that the performance of our solution comes very close to that of a state-of-the art solution. For each of these applications, we analyze the problem, illustrate the development of a logic-based model and explore how alternatives can affect the performance.

@article{labarre-idp3, author = {Blockeel, Hendrik and Bogaerts, Bart and Bruynooghe, Maurice and De Cat, Broes and De Pooter, Stef and Denecker, Marc and Jansen, Joachim and Labarre, Anthony and Ramon, Jan and Verwer, Sicco}, title = {Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with {IDP3}}, journal = {Theory and Practice of Logic Programming}, volume = {15}, number = {6}, month = nov, year = {2015}, pages = {783--817}, doi = {10.1017/S147106841400009X}, pdf = {publications/tplp2014.pdf}, url_Paper = "publications/tplp2014.pdf", url_arXiv = {http://arxiv.org/abs/1309.6883}, timestamp = {Tue, 26 Aug 2014 10:41:12 +0200}, abstract = { This paper provides a gentle introduction to problem solving with the IDP3 system. The core of IDP3 is a finite model generator that supports first order logic enriched with types, inductive definitions, aggregates and partial functions. It offers its users a modeling language that is a slight extension of predicate logic and allows them to solve a wide range of search problems. Apart from a small introductory example, applications are selected from problems that arose within machine learning and data mining research. These research areas have recently shown a strong interest in declarative modeling and constraint solving as opposed to algorithmic approaches. The paper illustrates that the IDP3 system can be a valuable tool for researchers with such an interest. The first problem is in the domain of stemmatology, a domain of philology concerned with the relationship between surviving variant versions of text. The second problem is about a somewhat related problem within biology where phylogenetic trees are used to represent the evolution of species. The third and final problem concerns the classical problem of learning a minimal automaton consistent with a given set of strings. For this last problem, we show that the performance of our solution comes very close to that of a state-of-the art solution. For each of these applications, we analyze the problem, illustrate the development of a logic-based model and explore how alternatives can affect the performance.}, biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/BruynoogheBBCPJLRDV13}, bibsource = {dblp computer science bibliography, http://dblp.org} } % 2013 ========================================================================

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