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Inductive Logic Programming

6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers

  • Conference proceedings
  • © 1997

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Editors:
  1. Stephen Muggleton
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1314)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ILP 1996.

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About this book

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.

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Table of contents (22 papers)

  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
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