A comparative study on ILP-based concept discovery systems

Kavurucu Y., Senkul P., TOROSLU İ. H.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.38, sa.9, ss.11598-11607, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 9
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.eswa.2011.03.038
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.11598-11607
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.