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Discovery Science

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Cover of 'Discovery Science'

Table of Contents

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    Book Overview
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    Chapter 1 Abduction and the Dualization Problem
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    Chapter 2 Signal Extraction and Knowledge Discovery Based on Statistical Modeling
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    Chapter 3 Association Computation for Information Access
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    Chapter 4 Efficient Data Representations That Preserve Information
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    Chapter 5 Can Learning in the Limit Be Done Efficiently?
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    Chapter 6 Discovering Frequent Substructures in Large Unordered Trees
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    Chapter 7 Discovering Rich Navigation Patterns on a Web Site
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    Chapter 8 Mining Frequent Itemsets with Category-Based Constraints
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    Chapter 9 Modelling Soil Radon Concentration for Earthquake Prediction
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    Chapter 10 Dialectical Evidence Assembly for Discovery
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    Chapter 11 Performance Analysis of a Greedy Algorithm for Inferring Boolean Functions
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    Chapter 12 Performance Evaluation of Decision Tree Graph-Based Induction
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    Chapter 13 Discovering Ecosystem Models from Time-Series Data
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    Chapter 14 An Optimal Strategy for Extracting Probabilistic Rules by Combining Rough Sets and Genetic Algorithm
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    Chapter 15 Extraction of Coverings as Monotone DNF Formulas
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    Chapter 16 What Kinds and Amounts of Causal Knowledge Can Be Acquired from Text by Using Connective Markers as Clues?
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    Chapter 17 Clustering Orders
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    Chapter 18 Business Application for Sales Transaction Data by Using Genome Analysis Technology
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    Chapter 19 Improving Efficiency of Frequent Query Discovery by Eliminating Non-relevant Candidates
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    Chapter 20 Chaining Patterns
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    Chapter 21 An Algorithm for Discovery of New Families of Optimal Regular Networks
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    Chapter 22 Enumerating Maximal Frequent Sets Using Irredundant Dualization
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    Chapter 23 Discovering Exceptional Information from Customer Inquiry by Association Rule Miner
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    Chapter 24 Automatic Classification for the Identification of Relationships in a Meta-Data Repository
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    Chapter 25 Effects of Unreliable Group Profiling by Means of Data Mining
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    Chapter 26 Using Constraints in Discovering Dynamics
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    Chapter 27 SA-Optimized Multiple View Smooth Polyhedron Representation NN
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    Chapter 28 Elements of an Agile Discovery Environment
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    Chapter 29 Discovery of User Preference in Personalized Design Recommender System through Combining Collaborative Filtering and Content Based Filtering
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    Chapter 30 Discovery of Relationships between Interests from Bulletin Board System by Dissimilarity Reconstruction
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    Chapter 31 A Genetic Algorithm for Inferring Pseudoknotted RNA Structures from Sequence Data
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    Chapter 32 Prediction of Molecular Bioactivity for Drug Design Using a Decision Tree Algorithm
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    Chapter 33 Mining RNA Structure Elements from the Structure Data of Protein-RNA Complexes
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    Chapter 34 Discovery of Cellular Automata Rules Using Cases
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    Chapter 35 Discovery of Web Communities from Positive and Negative Examples
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    Chapter 36 Association Rules and Dempster-Shafer Theory of Evidence
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    Chapter 37 Subgroup Discovery among Personal Homepages
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    Chapter 38 Collaborative Filtering Using Projective Restoration Operators
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    Chapter 39 Discovering Homographs Using N-Partite Graph Clustering
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    Chapter 40 Discovery of Trends and States in Irregular Medical Temporal Data
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    Chapter 41 Creating Abstract Concepts for Classification by Finding Top- N Maximal Weighted Cliques
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    Chapter 42 Content-Based Scene Change Detection of Video Sequence Using Hierarchical Hidden Markov Model
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    Chapter 43 An Appraisal of UNIVAUTO – The First Discovery Program to Generate a Scientific Article
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    Chapter 44 Scilog: A Language for Scientific Processes and Scales
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    Chapter 45 Mining Multiple Clustering Data for Knowledge Discovery
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    Chapter 46 Bacterium Lingualis – The Web-Based Commonsensical Knowledge Discovery Method
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    Chapter 47 Inducing Biological Models from Temporal Gene Expression Data
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    Chapter 48 Knowledge Discovery on Chemical Reactivity from Experimental Reaction Information
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    Chapter 49 A Method of Extracting Related Words Using Standardized Mutual Information
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    Chapter 50 Discovering Most Classificatory Patterns for Very Expressive Pattern Classes
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    Chapter 51 Mining Interesting Patterns Using Estimated Frequencies from Subpatterns and Superpatterns
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Title
Discovery Science
Published by
Springer Berlin Heidelberg, October 2003
DOI 10.1007/b14292
ISBNs
978-3-54-020293-6, 978-3-54-039644-4
Editors

Grieser, Gunter, Tanaka, Yuzuru, Yamamoto, Akihiro

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 14%
Norway 1 14%
Unknown 5 71%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Professor > Associate Professor 2 29%
Student > Ph. D. Student 2 29%
Professor 1 14%
Readers by discipline Count As %
Computer Science 6 86%
Business, Management and Accounting 1 14%