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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
Attention for Chapter 23: Representing Large Concept Hierarchies Using Lattice Data Structure
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Chapter title
Representing Large Concept Hierarchies Using Lattice Data Structure
Chapter number 23
Book title
Advances in Knowledge Discovery and Data Mining
Published by
Springer, Berlin, Heidelberg, April 2001
DOI 10.1007/3-540-45357-1_23
Book ISBNs
978-3-54-041910-5, 978-3-54-045357-4
Authors

Yanee Kachai, Kitsana Waiyamai

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 20%
Unknown 4 80%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 20%
Student > Bachelor 1 20%
Student > Ph. D. Student 1 20%
Student > Master 1 20%
Professor > Associate Professor 1 20%
Other 0 0%
Readers by discipline Count As %
Computer Science 5 100%