Discovery Science : 4th International Conference, DS 2001, Washington, DC, USA, November 25-28, 2001 Proceedings / edited by Klaus P. Jantke, Ayumi Shinohara.

Format:

Book

Contributor:

Jantke, K. P. (Klaus P.), editor.

Shinohara, Ayumi, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 2226.

Lecture Notes in Artificial Intelligence ; 2226

Language:

English

Subjects (All):

Artificial intelligence.

Philosophy and science.

Database management.

Information storage and retrieval.

Information technology.

Business--Data processing.

Business.

Artificial Intelligence.

Philosophy of Science.

Database Management.

Information Storage and Retrieval.

IT in Business.

Local Subjects:

Artificial Intelligence.

Philosophy of Science.

Database Management.

Information Storage and Retrieval.

IT in Business.

Physical Description:

1 online resource (XII, 500 pages).

Edition:

First edition 2001.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001.

System Details:

text file PDF

Summary:

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 (compare 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.

Contents:

Invited Papers

The Discovery Science Project in Japan

Discovering Mechanisms: A Computational Philosophy of Science Perspective

Queries Revisited

Inventing Discovery Tools: Combining Information Visualization with Data Mining

Robot Baby 2001

Regular Papers

VML: A View Modeling Language for Computational Knowledge Discovery

Computational Discovery of Communicable Knowledge: Symposium Report

Bounding Negative Information in Frequent Sets Algorithms

Functional Trees

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

Clipping and Analyzing News Using Machine Learning Techniques

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

Eliminating Useless Parts in Semi-structured Documents Using Alternation Counts

Multicriterially Best Explanations

Constructing Approximate Informative Basis of Association Rules

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

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

An Integrated Framework for Extended Discovery in Particle Physics

Stimulating Discovery

Assisting Model-Discovery in Neuroendocrinology

A General Theory of Deduction,Induction,and Learning

Learning Conformation Rules

Knowledge Navigation on Visualizing Complementary Documents

KeyWorld:Extracting Keywords from Document s Small World

A Method for Discovering Purified Web Communities

Divide and Conquer Machine Learning for a Genomics Analogy Problem

Towards a Method of Searching a Diverse Theory Space for Scientific Discovery

Effcient Local Search in Conceptual Clustering

Computational Revision of Quantitative Scientific Models

An Efficient Derivation for Elementary Formal Systems Based on Partial Unification

Worst-Case Analysis of Rule Discovery

Mining Semi-structured Data by Path Expressions

Theory Revision in Equation Discovery

Simplified Training Algorithms for Hierarchical Hidden Markov Models

Discovering Repetitive Expressions and Affinities from Anthologies of Classical Japanese Poems

Poster Papers

Web Site Rating and Improvement Based on Hyperlink Structure

A Practical Algorithm to Find the Best Episode Patterns

Interactive Exploration of Time Series Data

Clustering Rules Using Empirical Similarity of Support Sets

Computational Lessons from a Cognitive Study of Invention

Component-Based Framework for Virtual Information Materialization

Dynamic Aggregation to Support Pattern Discovery: A Case Study with Web Logs

Separation of Photoelectrons via Multivariate Maxwellian Mixture Model

Logic of Drug Discovery: A Descriptive Model of a Practice in Neuropharmacology

SCOOP: A Record Extractor without Knowledge on Input

Meta-analysis of Mutagenes Discovery.

Other Format:

Printed edition:

ISBN:

978-3-540-45650-6

9783540456506

Access Restriction:

Restricted for use by site license.