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Discovery Science

Overview of attention for book
Cover of 'Discovery Science'

Table of Contents

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    Book Overview
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    Chapter 1 The Discovery Science Project in Japan
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    Chapter 2 Discovering Mechanisms: A Computational Philosophy of Science Perspective
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    Chapter 3 Queries Revisited
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    Chapter 4 Inventing Discovery Tools: Combining Information Visualization with Data Mining
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    Chapter 5 Robot Baby 2001
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    Chapter 6 VML: A View Modeling Language for Computational Knowledge Discovery
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    Chapter 7 Computational Discovery of Communicable Knowledge: Symposium Report
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    Chapter 8 Bounding Negative Information in Frequent Sets Algorithms
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    Chapter 9 Functional Trees
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    Chapter 10 Spherical Horses and Shared Toothbrushes: Lessons Learned from a Workshop on Scientific and Technological Thinking
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    Chapter 11 Clipping and Analyzing News Using Machine Learning Techniques
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    Chapter 12 Towards Discovery of Deep and Wide First-Order Structures: A Case Study in the Domain of Mutagenicity
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    Chapter 13 Eliminating Useless Parts in Semi-structured Documents Using Alternation Counts
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    Chapter 14 Multicriterially Best Explanations
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    Chapter 15 Constructing Approximate Informative Basis of Association Rules
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    Chapter 16 Passage-Based Document Retrieval as a Tool for Text Mining with User’s Information Needs
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    Chapter 17 Automated Formulation of Reactions and Pathways in Nuclear Astrophysics: New Results
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    Chapter 18 An Integrated Framework for Extended Discovery in Particle Physics
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    Chapter 19 Stimulating Discovery
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    Chapter 20 Assisting Model-Discovery in Neuroendocrinology
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    Chapter 21 A General Theory of Deduction,Induction,and Learning
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    Chapter 22 Learning Conformation Rules
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    Chapter 23 Knowledge Navigation on Visualizing Complementary Documents
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    Chapter 24 KeyWorld:Extracting Keywords from Document s Small World
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    Chapter 25 A Method for Discovering Purified Web Communities
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    Chapter 26 Divide and Conquer Machine Learning for a Genomics Analogy Problem
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    Chapter 27 Towards a Method of Searching a Diverse Theory Space for Scientific Discovery
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    Chapter 28 Effcient Local Search in Conceptual Clustering
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    Chapter 29 Computational Revision of Quantitative Scientific Models
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    Chapter 30 An Efficient Derivation for Elementary Formal Systems Based on Partial Unification
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    Chapter 31 Worst-Case Analysis of Rule Discovery
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    Chapter 32 Mining Semi-structured Data by Path Expressions
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    Chapter 33 Theory Revision in Equation Discovery
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    Chapter 34 Simplified Training Algorithms for Hierarchical Hidden Markov Models
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    Chapter 35 Discovering Repetitive Expressions and Affinities from Anthologies of Classical Japanese Poems
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    Chapter 36 Web Site Rating and Improvement Based on Hyperlink Structure
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    Chapter 37 A Practical Algorithm to Find the Best Episode Patterns
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    Chapter 38 Interactive Exploration of Time Series Data
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    Chapter 39 Clustering Rules Using Empirical Similarity of Support Sets
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    Chapter 40 Computational Lessons from a Cognitive Study of Invention
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    Chapter 41 Component-Based Framework for Virtual Information Materialization
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    Chapter 42 Dynamic Aggregation to Support Pattern Discovery: A Case Study with Web Logs
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    Chapter 43 Separation of Photoelectrons via Multivariate Maxwellian Mixture Model
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    Chapter 44 Logic of Drug Discovery: A Descriptive Model of a Practice in Neuropharmacology
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    Chapter 45 SCOOP: A Record Extractor without Knowledge on Input
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    Chapter 46 Meta-analysis of Mutagenes Discovery
Attention for Chapter 6: VML: A View Modeling Language for Computational Knowledge Discovery
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Citations

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Chapter title
VML: A View Modeling Language for Computational Knowledge Discovery
Chapter number 6
Book title
Discovery Science
Published by
Springer, Berlin, Heidelberg, November 2001
DOI 10.1007/3-540-45650-3_6
Book ISBNs
978-3-54-042956-2, 978-3-54-045650-6
Authors

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

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 17%
Professor > Associate Professor 1 17%
Other 1 17%
Student > Postgraduate 1 17%
Unknown 2 33%
Readers by discipline Count As %
Computer Science 3 50%
Unknown 3 50%

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