A comparative study on ILP-based concept discovery systems


Kavurucu Y., Senkul P., TOROSLU İ. H.

EXPERT SYSTEMS WITH APPLICATIONS, vol.38, no.9, pp.11598-11607, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 9
  • Publication Date: 2011
  • Doi Number: 10.1016/j.eswa.2011.03.038
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.11598-11607
  • Middle East Technical University Affiliated: Yes

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 (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. (C) 2011 Elsevier Ltd. All rights reserved.