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Progress in Discovery Science

Final Report of the Japanese Discovery Science Project

  • Book
  • © 2002

Overview

Editors:
  1. Setsuo Arikawa

    1. Department of Informatics, Kyushu University, Fukuoka, Japan

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  2. Ayumi Shinohara

    1. Department of Informatics, Kyushu University, Fukuoka, Japan

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2281)

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

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Table of contents (52 chapters)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. Searching for Mutual Exclusion Algorithms Using BDDs

    • Koichi Takahashi, Masami Hagiya
    Pages 1-18

  3. Reducing Search Space in Solving Higher-Order Equations

    • Tetsuo Ida, Mircea Marin, Taro Suzuki
    Pages 19-30

  4. The Structure of Scientific Discovery: From a Philosophical Point of View

    • Keiichi Noé
    Pages 31-39

  5. Ideal Concepts, Intuitions, and Mathematical Knowledge Acquisitions in Husserl and Hilbert

    • Mitsuhiro Okada
    Pages 40-77

  6. Theory of Judgments and Derivations

    • Masahiko Sato
    Pages 78-122

  7. Efficient Data Mining from Large Text Databases

    • Hiroki Arimura, Hiroshi Sakamoto, Setsuo Arikawa
    Pages 123-139

  8. A Computational Model for Children’s Language Acquisition Using Inductive Logic Programming

    • Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki, Mutsumi Imai
    Pages 140-155

  9. Some Criterions for Selecting the Best Data Abstractions

    • Makoto Haraguchi, Yoshimitsu Kudoh
    Pages 156-167

  10. Discovery of Chances Underlying Real Data

    • Yukio Ohsawa
    Pages 168-177

  11. Towards the Integration of Inductive and Nonmonotonic Logic Programming

    • Chiaki Sakama
    Pages 178-188

  12. EM Learning for Symbolic-Statistical Models in Statistical Abduction

    • Taisuke Sato
    Pages 189-200

  13. Refutable/Inductive Learning from Neighbor Examples and Its Application to Decision Trees over Patterns

    • Masako Sato, Yasuhito Mukouchi, Mikiharu Terada
    Pages 201-213

  14. Constructing a Critical Casebase to Represent a Lattice-Based Relation

    • Ken Satoh
    Pages 214-223

  15. On Dimension Reduction Mappings for Approximate Retrieval of Multi-dimensional Data

    • Takeshi Shinohara, Hiroki Ishizaka
    Pages 224-231

  16. Rule Discovery from fMRI Brain Images by Logical Regression Analysis

    • Hiroshi Tsukimoto, Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi
    Pages 232-245

  17. A Theory of Hypothesis Finding in Clausal Logic

    • Akihiro Yamamoto, Bertram Fronhöfer
    Pages 246-257

  18. Efficient Data Mining by Active Learning

    • Hiroshi Mamitsuka, Naoki Abe
    Pages 258-267

  19. Data Compression Method Combining Properties of PPM and CTW

    • Takumi Okazaki, Kunihiko Sadakane, Hiroshi Imai
    Pages 268-283

  20. Discovery of Definition Patterns by Compressing Dictionary Sentences

    • Masatoshi Tsuchiya, Sadao Kurohashi, Satoshi Sato
    Pages 284-295
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Editors and Affiliations

  • Department of Informatics, Kyushu University, Fukuoka, Japan

    Setsuo Arikawa, Ayumi Shinohara

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