A comparative study on ILP-based concept discovery systems

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 (CD)-D-2 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.

Citation Formats
Y. Kavurucu, P. Karagöz, and İ. H. Toroslu, “A comparative study on ILP-based concept discovery systems,” EXPERT SYSTEMS WITH APPLICATIONS, vol. 38, no. 9, pp. 11598–11607, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32734.