A comparative study on ILP-based concept discovery systems |
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Authors: | Y Kavurucu P Senkul IH Toroslu |
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Affiliation: | 1. School of ECE, College of Engineering, University of Tehran, Tehran, Iran;2. School of CSEE, University of Essex, UK |
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Abstract: | Inductive Logic Programming (ILP) studies learning from examples, within the framework provided by clausal logic. ILP has become a popular subject in the field of data mining due to its ability to discover patterns in relational domains. Several ILP-based concept discovery systems are developed which employs various search strategies, heuristics and language pattern limitations. LINUS, GOLEM, CIGOL, MIS, FOIL, PROGOL, ALEPH and WARMR are well-known ILP-based systems. In this work, firstly introductory information about ILP is given, and then the above-mentioned systems and an ILP-based concept discovery system called C2D are briefly described and the fundamentals of their mechanisms are demonstrated on a running example. Finally, a set of experimental results on real-world problems are presented in order to evaluate and compare the performance of the above-mentioned systems. |
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