Discovery Science

1. Front Matter

   Pages I-XII

   PDF

2. Invited Papers

   1. The Discovery Science Project in Japan

      • Setsuo Arikawa

      Pages 1-2

   2. Discovering Mechanisms: A Computational Philosophy of Science Perspective

      • Lindley Darden

      Pages 3-15

   3. Queries Revisited

      • Dana Angluin

      Pages 16-16

   4. Inventing Discovery Tools: Combining Information Visualization with Data Mining

      • Ben Shneiderman

      Pages 17-28

   5. Robot Baby 2001

      • Paul R. Cohen, Tim Oates, Niall Adams, Carole R. Beal

      Pages 29-29

3. Regular Papers

   1. VML: A View Modeling Language for Computational Knowledge Discovery

      • Hideo Bannai, Yoshinori Tamada, Osamu Maruyama, Satoru Miyano

      Pages 30-44

   2. Computational Discovery of Communicable Knowledge: Symposium Report

      • Sašo Džeroski, Pat Langley

      Pages 45-49

   3. Bounding Negative Information in Frequent Sets Algorithms

      • I. Fortes, J. L. Balcázar, R. Morales

      Pages 50-58

   4. Functional Trees

      • João Gama

      Pages 59-73

   5. Spherical Horses and Shared Toothbrushes: Lessons Learned from a Workshop on Scientific and Technological Thinking

      • Michael E. Gorman, Alexandra Kincannon, Matthew M. Mehalik

      Pages 74-86

   6. Clipping and Analyzing News Using Machine Learning Techniques

      • Hans Gründel, Tino Naphtali, Christian Wiech, Jan-Marian Gluba, Maiken Rohdenburg, Tobias Scheffer

      Pages 87-99

   7. Towards Discovery of Deep and Wide First-Order Structures: A Case Study in the Domain of Mutagenicity

      • Tamás Horváth, Stefan Wrobel

      Pages 100-112

   8. Eliminating Useless Parts in Semi-structured Documents Using Alternation Counts

      • Daisuke Ikeda, Yasuhiro Yamada, Sachio Hirokawa

      Pages 113-127

   9. Multicriterially Best Explanations

      • Naresh S. Iyer, John R. Josephson

      Pages 128-140

   10. Constructing Approximate Informative Basis of Association Rules

       • Kouta Kanda, Makoto Haraguchi, Yoshiaki Okubo

       Pages 141-154

   11. Passage-Based Document Retrieval as a Tool for Text Mining with User’s Information Needs

       • Koichi Kise, Markus Junker, Andreas Dengel, Keinosuke Matsumoto

       Pages 155-169

   12. Automated Formulation of Reactions and Pathways in Nuclear Astrophysics: New Results

       • Sakir Kocabas

       Pages 170-181

   13. An Integrated Framework for Extended Discovery in Particle Physics

       • Sakir Kocabas, Pat Langley

       Pages 182-195

   14. Stimulating Discovery

       • Ronald N. Kosto

       Pages 196-213

These are the conference proceedings of the 4th International Conference on Discovery Science (DS 2001). Although discovery is naturally ubiquitous in s- ence, and scientific discovery itself has been subject to scientific investigation for centuries, the term Discovery Science is comparably new. It came up in conn- tion with the Japanese Discovery Science project (cf. Arikawa's invited lecture on The Discovery Science Project in Japan in the present volume) some time during the last few years. Setsuo Arikawa is the father in spirit of the Discovery Science conference series. He led the above mentioned project, and he is currently serving as the chairman of the international steering committee for the Discovery Science c- ference series. The other members of this board are currently (in alphabetical order) Klaus P. Jantke, Masahiko Sato, Ayumi Shinohara, Carl H. Smith, and Thomas Zeugmann. Colleagues and friends from all over the world took the opportunity of me- ing for this conference to celebrate Arikawa's 60th birthday and to pay tribute to his manifold contributions to science, in general, and to Learning Theory and Discovery Science, in particular. Algorithmic Learning Theory (ALT, for short) is another conference series initiated by Setsuo Arikawa in Japan in 1990. In 1994, it amalgamated with the conference series on Analogical and Inductive Inference (AII), when ALT was held outside of Japan for the first time.

• Classifier Systems
• Computational Learning
• Data Analysis
• Discovery
• Internet Information Retrieval
• Machine Learning
• Pattern Recognition
• Schema Discovery
• Text Mining
• agents
• algorithms
• data mining
• learning
• science
• visualization

• DFKI GmbH Saarbrücken, Saarbrücken, Germany

  Klaus P. Jantke

• Department of Informatics, Kyushu University, Fukuoka, Japan

  Ayumi Shinohara

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