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Inductive Logic Programming

16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. Stephen Muggleton
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  2. Ramon Otero
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  3. Alireza Tamaddoni-Nezhad
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4455)

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

Included in the following conference series:

Conference proceedings info: ILP 2006.

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Table of contents (39 papers)

  1. Front Matter

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  2. Invited Papers

    1. Actions, Causation and Logic Programming

      • Vladimir Lifschitz
      Pages 1-1

    2. Challenges to Machine Learning: Relations Between Reality and Appearance

      • John McCarthy
      Pages 2-9

    3. First-Order Probabilistic Languages: Into the Unknown

      • Brian Milch, Stuart Russell
      Pages 10-24

    4. Integration of Learning and Reasoning Techniques

      • Bart Selman
      Pages 25-25

    5. Injecting Life with Computers

      • Ehud Shapiro
      Pages 26-26

  3. Special Issue Extended Abstracts

    1. On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate

      • Erick Alphonse, Aomar Osmani
      Pages 27-29

    2. Revising Probabilistic Prolog Programs

      • Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen
      Pages 30-33

    3. Inductive Logic Programming for Gene Regulation Prediction

      • Sebastian Fröhler, Stefan Kramer
      Pages 34-36

    4. QG/GA: A Stochastic Search for Progol

      • Stephen Muggleton, Alireza Tamaddoni-Nezhad
      Pages 37-39

    5. Generalized Ordering-Search for Learning Directed Probabilistic Logical Models

      • Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
      Pages 40-42

    6. ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions

      • Fabrizio Riguzzi
      Pages 43-45

    7. Margin-Based First-Order Rule Learning

      • Ulrich Rückert, Stefan Kramer
      Pages 46-48

  4. Research Papers

    1. Extension of the Top-Down Data-Driven Strategy to ILP

      • Erick Alphonse, Céline Rouveirol
      Pages 49-63

    2. Extracting Requirements from Scenarios with ILP

      • Dalal Alrajeh, Oliver Ray, Alessandra Russo, Sebastian Uchitel
      Pages 64-78

    3. Learning Recursive Patterns for Biomedical Information Extraction

      • Margherita Berardi, Donato Malerba
      Pages 79-93

    4. Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks

      • Hendrik Blockeel, Wannes Meert
      Pages 94-108

    5. Multi-class Prediction Using Stochastic Logic Programs

      • Jianzhong Chen, Lawrence Kelley, Stephen Muggleton, Michael Sternberg
      Pages 109-124

    6. Structuring Natural Language Data by Learning Rewriting Rules

      • Guillaume Cleuziou, Lionel Martin, Christel Vrain
      Pages 125-138

    7. An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification

      • Koichiro Doi, Tetsuya Yamashita, Akihiro Yamamoto
      Pages 139-153
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About this book

The inherent dangers of change are often summed up in the misquoted Chinese curse “May you live in interesting times.” The submission procedure for the 16th International Conference of Inductive Logic Programming (ILP 2006) was a radical (hopefully interesting but not cursed) departure from previous years. Submissions were requested in two phases. The ?rst phase involved submission of short papers (three pages) which were then presented at the conference and included in a short papers proceedings. In the second phase, reviewers selected papersforlongpapersubmission(15pagesmaximum).Thesewerethenassessed by the same reviewers, who then decided which papers to include in the journal special issue and proceedings. In the ?rst phase there were a record 77 papers, comparedto the usual20 orso long papersofpreviousyears.Eachpaper was- viewed by three reviewers. Out of these, 71 contributors were invited to submit long papers. Out of the long paper submissions, 7 were selected for the - chine Learning Journal special issue and 27 were accepted for the proceedings. In addition, two papers were nominated by Program Committee referees for the applications prize and two for the theory prize. The papers represent the div- sity and vitality in present ILP research including ILP theory, implementations, search and phase transition, distributed and large-scale learning, probabilistic ILP, biological applications, natural language learning and planning and action learning.

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