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Progress in Discovery Science探索科学的进步

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Progress in Discovery Science探索科学的进步

最 低 价:¥279.50

定 价:¥310.55

作 者:SetsuoArikawa (Editor), AyumiShinohara (Editor) 著

出 版 社:Oversea Publishing House

出版时间:2002-4-1

I S B N:9783540433385

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内容简介

This book documents the scientific outcome and constitutes the final report of the Japanese reseach project on discovery science. During three years more than 60 scientists participated in the project and developed a wealth of new methods for knowledge discovery and data mining.
  The 52 revised full papers presented were carefully reviewed and span the whole range of knowledge discovery from logical foundations and inductive reasoning to statistical inference and computational learning. A broad va-riety of advanced applications are presented including knowledge discovery and data mining in very large databases, knowledge discovery in network environments, text mining, information extraction, rule mining, Web mining, image processing, and pattern recognition,etc.

作者简介

目录

Searching for Mutual Exclusion Algorithms Using BDDs
Reducing Search Space in Solving Higher-Order Equations
The Structure of Scientific Discovery:From a Philosophical Point of View
Ideal Concepts,Intuitions,and Mathematical Knowledge Acquisitions in Husserl and Hilbert
Theory of Judgments and Derivations
Efficient Data Mining from Large Text Databases
A Computational Model for Children’S Language Acquisition Using Inductive Logic Programming
Some Criterions for Selecting the Best Data Abstractions
Discovery of Chances Underlying Real Data
Towards the Integration of Inductive and Nonmonotonic Logic Programming
EM Learning for Symbolic-Statistical Models in Statistical Abduction
Refutable/Inductive Learning from Neighbor Examples and Its Application to Decision Trees over Patterns
Constructing a Critical Casebase to Represent a Lattice-Based Relation
On Dimension Reduction Mappings for Approximate Retrieval of Multi-dimensional Data
Rule Discovery from fMRI Brain Images by Logical Regression Analysis
A Theory of Hypothesis Finding in Clausal Logic
Efficient Data Mining by Active Learning
Data Compression Method Combining Properties of PPM and CTW
Discovery of Definition Patterns by Compressing Dictionary Sentences
On-Line Algorithm to Predict Nearly as Well as the Best Pruning of a Decision Tree
Finding Best Patterns Practically
Classification of Object Sequences Using Syntactical Strucutere
Top-Down Decision Tree Boosting and Its Applications
Extraction of Primitive Motion and Discovery of Association Rules from Human Motion Data
Algorithmic Aspects of Boosting
Automatic Detection of Geomagnetic Jerks by Applying a Statistical Time Series Model to Geomagnetic Monthly Means
Application of Multivariate Maxwellian Mixture Model to Plasma Velocity Distribution
……

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