Inductive Logic Programming

1. Front Matter

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2. Inductive logic programming for natural language processing

   • Raymond J. Mooney

   Pages 1-22

3. An initial experiment into stereochemistry-based drug design using inductive logic programming

   • Stephen Muggleton, David Page, Ashwin Srinivasan

   Pages 23-40

4. Applying ILP to diterpene structure elucidation from 13C NMR spectra

   • Sašo Džeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck

   Pages 41-54

5. Analysis and prediction of piano performances using inductive logic programming

   • Erika Van Baelen, Luc De Raedt

   Pages 55-71

6. Noise detection and elimination applied to noise handling in a KRK chess endgame

   • Dragan Gamberger, Nada Lavrač

   Pages 72-88

7. Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes

   • Ashwin Srinivasan, Ross.D. King

   Pages 89-104

8. Polynomial-time learning in logic programming and constraint logic programming

   • Michèle Sebag, Céline Rouveirol

   Pages 105-126

9. Analyzing and learning ECG waveforms

   • Gabriella Kókai, Zoltán Alexin, Tibor Gyimóthy

   Pages 127-145

10. Learning rules that classify ocular fundus images for glaucoma diagnosis

    • Fumio Mizoguchi, Hayato Ohwada, Makiko Daidoji, Shiroteru Shirato

    Pages 146-159

11. A new design and implementation of progol by bottom-up computation

    • Hiroshi Fujita, Naoki Yagi, Tomonobu Ozaki, Koichi Furukawa

    Pages 161-174

12. Inductive logic program synthesis with DIALOGS

    • Pierre Flener

    Pages 175-198

13. Relational knowledge discovery in databases

    • Hendrik Blockeel, Luc De Raedt

    Pages 199-211

14. Efficient θ-subsumption based on graph algorithms

    • Tobias Scheffer, Ralf Herbrich, Fritz Wysotzki

    Pages 212-228

15. Integrity constraints in ILP using a Monte Carlo approach

    • Alípio Jorge, Pavel B. Brazdil

    Pages 229-244

16. Restructuring chain datalog programs

    • Anke Rieger

    Pages 245-264

17. Top-down induction of logic programs from incomplete samples

    • Nobuhiro Inuzuka, Masakage Kamo, Naohiro Ishii, Hirohisa Seki, Hidenori Itoh

    Pages 265-282

18. Least generalizations under implication

    • Shan-Hwei Nienhuys-Cheng, Ronald de Wolf

    Pages 283-298

19. Efficient proof encoding

    • Uroš Pompe

    Pages 299-314

20. Learning Logic programs with random classification noise

    • Tamás Horváth, Robert H. Sloan, György Turán

    Pages 315-336

This book constitutes the strictly refereed post-workshop proceedings of the 6th International Workshop on Inductive Logic Programming, ILP-96, held in Stockholm, Sweden, in August 1996.
The 21 full papers were carefully reviewed and selected for inclusion in the book in revised version. Also included is the invited contribution "Inductive logic programming for natural language processing" by Raymond J. Mooney. Among the topics covered are natural language learning, drug design, NMR and ECG analysis, glaucoma diagnosis, efficiency measures for implementations and database interaction, program synthesis, proof encoding and learning in the absence of negative data, and least generalizations under implication ordering.

• inductive learning
• inductive logic programming
• learning
• logic
• machine learning
• natural language processing
• programming
• strategic learning

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