Scaling up inductive logic programming by learning from interpretations

Data Mining and Knowledge Discovery

Volumn 3, Issue 1, 1999, Pages 59-93

  Blockeel, Hendrik ^a   De Raedt, Luc ^a   Jacobs, Nico ^a   Demoen, Bart ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

First order decision trees; Inductive logic programming; Knowledge discovery in databases; Learning from interpretations

Indexed keywords

EID: 22644449312     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1009867806624     Document Type: Article

References (24)

1. Agrawal, R., H. Mannila, H., Srikant, R., Toivonen, H. and Verkamo, A.I. 1996. Fast discovery of association rules. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 307-328. The MIT Press.
2. Blockeel, H. and De Raedt, L. 1997. Lookahead and discretization in ILP. In Proceedings of the 7th International Workshop on Inductive Logic Programming, volume 1297 of Lecture Notes in Artificial Intelligence, pages 77-85. Springer-Verlag.
3. Blockeel, H. and De Raedt, L. 1998. Top-down induction of first order logical decision trees. Artificial Intelligence, 101(1-2):285-297.
4. Blockeel, H., De Raedt, L. and Ramon, J. 1998. Top-down induction of clustering trees. In Proceedings of the 15th International Conference on Machine Learning, pages 55-63. http://www.cs.kuleuven.ac.be/∼ml/PS/ML 98-56 . ps.
5. Bongard, M. 1970. Pattern Recognition. Spartan Books.
6. Bratko, I. 1990. Prolog Programming for Artificial Intelligence. Addison-Wesley. 2nd Edition.
7. Bratko, I. and Muggleton, S. 1995. Applications of inductive logic programming. Communications of the ACM, 38(11):65-70.
8. Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. 1984. Classification and Regression Trees. Wadsworth, Belmont.
9. Cohen, W.W. 1995. Pac-learning recursive logic programs: Negative results. Journal of Artificial Intelligence Research, 2:541-573.
10. Cohen, W.W. and Page, D. 1995. Polynomial learnability and inductive logic programming: methods and results. New Generation Computing, 13.
11. Cussens, J. 1997. Part-of-speech tagging using progol. In Proceedings of the 7th International Workshop on Inductive Logic Programming, volume 1297 of Lecture Notes in Artificial Intelligence, pages 93-108. Springer-Verlag.
12. De Raedt, L., editor. 1996. Advances in Inductive Logic Programming, volume 32 of Frontiers in Artificial Intelligence and Applications. IOS Press.
13. De Raedt, L. 1997. Logical settings for concept learning. Artificial Intelligence, 95:187-201.
14. De Raedt, L. 1998. Attribute-value learning versus inductive logic programming: the missing links (extended abstract). In Proceedings of the 8th International Conference on Inductive Logic Programming, volume 1446 of Lecture Notes in Artificial Intelligence, pages 1-8. Springer-Verlag.
15. De Raedt, L., Blockeel, H., Dehaspe, L. and Van Laer, W. 1998. Three companions for first order data mining. In S. Džeroski and N. Lavrač, editors, Inductive Logic Programming for Knowledge Discovery in Databases, Lecture Notes in Artificial Intelligence. Springer-Verlag. To appear.
16. De Raedt, L. and Dehaspe, L. 1997. Clausal discovery. Machine Learning, 26:99-146.
17. De Raedt, L. and Džeroski, S. 1994. First order jk-clausal theories are PAC-learnable. Artificial Intelligence, 70:375-392.
18. De Raedt, L. and Van Laer, W. 1995. Inductive constraint logic. In Klaus P. Jantke, Takeshi Shinohara, and Thomas Zeugmann, editors, Proceedings of the 6th International Workshop on Algorithmic Learning Theory, volume 997 of Lecture Notes in Artificial Intelligence, pages 80-94. Springer-Verlag.
19. Dehaspe, L. and De Raedt, L. 1997. Mining association rules in multiple relations. In Proceedings of the 7th International Workshop on Inductive Logic Programming, volume 1297 of Lecture Notes in Artificial Intelligence, pages 125-132. Springer-Verlag.
20. Dietterich, T. G., Lathrop, R.H. and Lozano-Pérez, T. 1997. Solving the multiple-instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31-71.
21. Dougherty, J., Kohavi, R. and Sahami, M. 1995. Supervised and unsupervised discretization of continuous features. In A. Prieditis and S. Russell, editors, Proc. Twelfth International Conference on Machine Learning. Morgan Kaufmann.
22. Džeroski, S., Muggleton, S. and Russell, S. 1992. PAC-learnability of determinate logic programs. In Proceedings of the 5th ACM workshop on Computational Learning Theory, pages 128-135.
23. Elmasri, R. and Navathe, S.B. 1989. Fundamentals of Database Systems. The Benjamin/Cummings Publishing Company, 2nd edition.
24. Fayyad, U.M. and Irani, K.B. 1993. Multi-interval discretization of continuous-valued attributes for classification learning. In Proceedings of the 13th International Joint Conference on Artificial Intelligence, pages 1022-1027, San Mateo, CA. Morgan Kaufmann.