Inductive Logic Programming 2Inductive logic programming (ILP) is a research area lying at the intersection of inductive machine learning and logic programming. The general aim of ILP is to develop theories, techniques and applications of inductive learning from observations and background knowledge in a first order logical framework. The ILP2 project is an ESPRIT Long Term Research project which started on January 1, 1996, and lasts for 3 years. It continues the ILP project (September 1992 - August 1995). Further general information about the ILP2 project can be found on the ILP2 home page. The following is a description of the work done at Bristol.
Recent work has concentrated on the realisation of a practical system for descriptive induction of integrity constraints, that can be applied to real-world data mining tasks (Flach, 1997; Flach & Lachiche, 1997). A first release of the Tertius system is now available. Furthermore, we have investigated the use of a strongly typed language as conceptual basis for ILP (Flach, Giraud-Carrier & Lloyd, 1998). This line of research has resulted in the 1BC first-order Bayesian classifier (Flach & Lachiche, 1999). Finally, we have continued previous work on logical characterisation of inductive reasoning (Flach, 1998).
Staff and StudentsPeter Flach, Christophe Giraud-Carrier, Nicolas Lachiche, and Torbjorn Dahl.
- P.A. Flach and N. Lachiche. 1BC: a first-order Bayesian classifier. In 9th International Conference on Inductive Logic Programming (ILP-99), pp. 92--103. LNAI 1634, Springer-Verlag, 1999.
- T. S. Dahl. Background Knowledge in the Tertius First Order Knowledge Discovery Tool Technical Report CSTR-99-006, Department of Computer Science, University of Bristol, March 1999.
- P. A. Flach, C. Giraud-Carrier, and J. W. Lloyd. Strongly Typed Inductive Concept Learning. In 8th International Conference on Inductive Logic Programming (ILP-98), pp. 185--194. LNAI 1446, Springer-Verlag, 1998.
- P.A. Flach. Comparing consequence relations. In Principles of Knowledge Representation and Reasoning: Proceedings of the Sixth International Conference (KR'98), pp. 180--189. Morgan Kaufmann, 1998.
- P.A. Flach and N. Lachiche. Cooking up integrity constraints with PRIMUS (preliminary report). Technical Report CSTR-97-009, Department of Computer Science, University of Bristol, December 1997.
- P.A. Flach. Normal forms for Inductive Logic Programming. In Proc. Seventh Inductive Logic Programming Workshop, N. Lavrac and Saso Dzeroski (eds.), pp.149--156. LNAI 1297, Springer-Verlag, 1997.