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Advances in Knowledge Discovery and Data Mining

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Cover of 'Advances in Knowledge Discovery and Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Data Mining as an Automated Service
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    Chapter 2 Trends and Challenges in the Industrial Applications of KDD
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    Chapter 3 Finding Event-Oriented Patterns in Long Temporal Sequences
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    Chapter 4 Mining Frequent Episodes for Relating Financial Events and Stock Trends
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    Chapter 5 An Efficient Algorithm of Frequent Connected Subgraph Extraction
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    Chapter 6 Classifier Construction by Graph-Based Induction for Graph-Structured Data
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    Chapter 7 Comparison of the Performance of Center-Based Clustering Algorithms
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    Chapter 8 Automatic Extraction of Clusters from Hierarchical Clustering Representations
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    Chapter 9 Large Scale Unstructured Document Classification Using Unlabeled Data and Syntactic Information
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    Chapter 10 Extracting Shared Topics of Multiple Documents
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    Chapter 11 An Empirical Study on Dimensionality Optimization in Text Mining for Linguistic Knowledge Acquisition
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    Chapter 12 A Semi-supervised Algorithm for Pattern Discovery in Information Extraction from Textual Data
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    Chapter 13 Mining Patterns of Dyspepsia Symptoms Across Time Points Using Constraint Association Rules
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    Chapter 14 Predicting Protein Structural Class from Closed Protein Sequences
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    Chapter 15 Learning Rules to Extract Protein Interactions from Biomedical Text
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    Chapter 16 Predicting Protein Interactions in Human by Homologous Interactions in Yeast
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    Chapter 17 Mining the Customer’s Up-To-Moment Preferences for E-commerce Recommendation
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    Chapter 18 A Graph-Based Optimization Algorithm for Website Topology Using Interesting Association Rules
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    Chapter 19 A Markovian Approach for Web User Profiling and Clustering
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    Chapter 20 Extracting User Interests from Bookmarks on the Web
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    Chapter 21 Mining Frequent Instances on Workflows
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    Chapter 22 Real Time Video Data Mining for Surveillance Video Streams
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    Chapter 23 Distinguishing Causal and Acausal Temporal Relations
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    Chapter 24 Online Bayes Point Machines
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    Chapter 25 Exploiting Hierarchical Domain Values for Bayesian Learning
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    Chapter 26 A New Restricted Bayesian Network Classifier
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    Chapter 27 AGRID: An Efficient Algorithm for Clustering Large High-Dimensional Datasets
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    Chapter 28 Multi-level Clustering and Reasoning about Its Clusters Using Region Connection Calculus
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    Chapter 29 An Efficient Cell-Based Clustering Method for Handling Large, High-Dimensional Data
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    Chapter 30 Enhancing SWF for Incremental Association Mining by Itemset Maintenance
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    Chapter 31 Reducing Rule Covers with Deterministic Error Bounds
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    Chapter 32 Evolutionary Approach for Mining Association Rules on Dynamic Databases
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    Chapter 33 Position Coded Pre-order Linked WAP-Tree for Web Log Sequential Pattern Mining
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    Chapter 34 An Integrated System of Mining HTML Texts and Filtering Structured Documents
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    Chapter 35 A New Sequential Mining Approach to XML Document Similarity Computation
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    Chapter 36 Optimization of Fuzzy Rules for Classification Using Genetic Algorithm
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    Chapter 37 Fast Pattern Selection for Support Vector Classifiers
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    Chapter 38 Averaged Boosting: A Noise-Robust Ensemble Method
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    Chapter 39 Improving Performance of Decision Tree Algorithms with Multi-edited Nearest Neighbor Rule
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    Chapter 40 HOT: Hypergraph-Based Outlier Test for Categorical Data
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    Chapter 41 A Method for Aggregating Partitions, Applications in K.D.D.
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    Chapter 42 Efficiently Computing Iceberg Cubes with Complex Constraints through Bounding
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    Chapter 43 Extraction of Tag Tree Patterns with Contractible Variables from Irregular Semistructured Data
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    Chapter 44 Step-by-Step Regression: A More Efficient Alternative for Polynomial Multiple Linear Regression in Stream Cube
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    Chapter 45 Progressive Weighted Miner: An Efficient Method for Time-Constraint Mining
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    Chapter 46 Mining Open Source Software (OSS) Data Using Association Rules Network
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    Chapter 47 Parallel FP-Growth on PC Cluster
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    Chapter 48 Active Feature Selection Using Classes
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    Chapter 49 Electricity Based External Similarity of Categorical Attributes
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    Chapter 50 Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers
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    Chapter 51 Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach
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    Chapter 52 Considering Correlation between Variables to Improve Spatiotemporal Forecasting
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    Chapter 53 Correlation Analysis of Spatial Time Series Datasets: A Filter-and-Refine Approach
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    Chapter 54 When to Update the Sequential Patterns of Stream Data?
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    Chapter 55 A New Clustering Algorithm for Transaction Data via Caucus
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    Chapter 56 DBRS: A Density-Based Spatial Clustering Method with Random Sampling
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    Chapter 57 Optimized Clustering for Anomaly Intrusion Detection
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    Chapter 58 Finding Frequent Subgraphs from Graph Structured Data with Geometric Information and Its Application to Lossless Compression
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    Chapter 59 Upgrading ILP Rules to First-Order Bayesian Networks
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    Chapter 60 A Clustering Validity Assessment Index
Overall attention for this book and its chapters
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Mentioned by

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1 Wikipedia page

Citations

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45 Dimensions

Readers on

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7 Mendeley
Summary Wikipedia Dimensions citations
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Title
Advances in Knowledge Discovery and Data Mining
Published by
Springer Science & Business Media, April 2003
DOI 10.1007/3-540-36175-8
ISBNs
978-3-54-004760-5, 978-3-54-036175-6
Editors

Whang, Kyu-Young, Jeon, Jongwoo, Shim, Kyuseok, Srivastava, Jaideep

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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 %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 14%
Unknown 6 86%
Readers by discipline Count As %
Computer Science 1 14%
Unknown 6 86%

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