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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 40: Computational Lessons from a Cognitive Study of Invention
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Citations

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Chapter title
Computational Lessons from a Cognitive Study of Invention
Chapter number 40
Book title
Discovery Science
Published by
Springer, Berlin, Heidelberg, November 2001
DOI 10.1007/3-540-45650-3_40
Book ISBNs
978-3-54-042956-2, 978-3-54-045650-6
Authors

Marin Simina, Michael E. Gorman, Janet L. Kolodner, Simina, Marin, Gorman, Michael E., Kolodner, Janet L.

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Professor 1 33%
Student > Ph. D. Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Social Sciences 1 33%
Unknown 1 33%

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