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Advances in Knowledge Discovery and Data Mining

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Table of Contents

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    Book Overview
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    Chapter 1 Incompleteness in Data Mining
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    Chapter 2 Mining E-Commerce Data: The Good, the Bad, and the Ugly
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    Chapter 3 Seamless Integration of Data Mining with DBMS and Applications
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    Chapter 4 Applying Pattern Mining to Web Information Extraction
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    Chapter 5 Empirical Study of Recommender Systems Using Linear Classifiers
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    Chapter 6 iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping
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    Chapter 7 A Characterized Rating Recommend System
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    Chapter 8 Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents
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    Chapter 9 Text Categorization Using Weight Adjusted k -Nearest Neighbor Classification
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    Chapter 10 Predictive Self-Organizing Networks for Text Categorization
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    Chapter 11 Meta-learning Models for Automatic Textual Document Categorization
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    Chapter 12 Efficient Algorithms for Concept Space Construction
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    Chapter 13 Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks
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    Chapter 14 Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps
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    Chapter 15 Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis
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    Chapter 16 A Toolbox Approach to Flexible and Efficient Data Mining
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    Chapter 17 Determining Progression in Glaucoma Using Visual Fields
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    Chapter 18 Seabreeze Prediction Using Bayesian Networks
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    Chapter 19 Semi-supervised Learning in Medical Image Database
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    Chapter 20 On Application of Rough Data Mining Methods to Automatic Construction of Student Models
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    Chapter 21 Concept Approximation in Concept Lattice
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    Chapter 22 Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data
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    Chapter 23 Representing Large Concept Hierarchies Using Lattice Data Structure
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    Chapter 24 Feature Selection for Temporal Health Records
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    Chapter 25 Boosting the Performance of Nearest Neighbour Methods with Feature Selection
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    Chapter 26 Feature Selection for Meta-learning
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    Chapter 27 Efficient Mining of Niches and Set Routines
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    Chapter 28 Evaluation of Interestingness Measures for Ranking Discovered Knowledge
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    Chapter 29 Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data
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    Chapter 30 Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control
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    Chapter 31 Scalable Hierarchical Clustering Method for Sequences of Categorical Values
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    Chapter 32 FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences
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    Chapter 33 Sequential Index Structure for Content-Based Retrieval
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    Chapter 34 The S 2 -Tree: An Index Structure for Subsequence Matching of Spatial Objects
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    Chapter 35 Temporal Data Mining Using Hidden Markov-Local Polynomial Models
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    Chapter 36 Patterns Discovery Based on Time-Series Decomposition
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    Chapter 37 Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering
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    Chapter 38 Micro Similarity Queries in Time Series Database
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    Chapter 39 Mining Optimal Class Association Rule Set
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    Chapter 40 Generating Frequent Patterns with the Frequent Pattern List
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    Chapter 41 User-Defined Association Mining
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    Chapter 42 Direct and Incremental Computing of Maximal Covering Rules
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    Chapter 43 Towards Efficient Data Re-mining (DRM)
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    Chapter 44 Data Allocation Algorithm for Parallel Association Rule Discovery
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    Chapter 45 Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm
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    Chapter 46 Hierarchical Classification of Documents with Error Control
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    Chapter 47 An Efficient Data Compression Approach to the Classification Task
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    Chapter 48 Combining the Strength of Pattern Frequency and Distance for Classification
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    Chapter 49 A Scalable Algorithm for Rule Post-pruning of Large Decision Trees
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    Chapter 50 Optimizing the Induction of Alternating Decision Trees
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    Chapter 51 Building Behaviour Knowledge Space to Make Classification Decision
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    Chapter 52 Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions
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    Chapter 53 A Rough Set-Based Clustering Method with Modification of Equivalence Relations
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    Chapter 54 Importance of Individual Variables in the k -Means Algorithm
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    Chapter 55 A Hybrid Approach to Clustering in Very Large Databases
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    Chapter 56 A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method
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    Chapter 57 Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron
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    Chapter 58 Knowledge Acquisition from Both Human Expert and Data
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    Chapter 59 Neighborhood Dependencies for Prediction
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    Chapter 60 Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms
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    Chapter 61 Interactive Construction of Decision Trees
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    Chapter 62 An Improved Learning Algorithm for Augmented Naive Bayes
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    Chapter 63 Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data
Overall attention for this book and its chapters
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Mentioned by

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8 patents

Citations

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4 Dimensions

Readers on

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2 Mendeley
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Title
Advances in Knowledge Discovery and Data Mining
Published by
Springer Science & Business Media, April 2001
DOI 10.1007/3-540-45357-1
ISBNs
978-3-54-041910-5, 978-3-54-045357-4
Editors

David Cheung, Graham J. Williams, Qing Li

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 50%
Canada 1 50%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 150%
Researcher 3 150%
Other 3 150%
Student > Ph. D. Student 3 150%
Student > Doctoral Student 2 100%
Other 5 250%
Readers by discipline Count As %
Computer Science 15 750%
Engineering 2 100%
Unspecified 1 50%
Arts and Humanities 1 50%