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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

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Mining of Evolving Data Streams with Privacy Preservation
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    Chapter 2 Data Mining Grand Challenges
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    Chapter 3 Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms
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    Chapter 4 Spectral Energy Minimization for Semi-supervised Learning
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    Chapter 5 Discriminative Methods for Multi-labeled Classification
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    Chapter 6 Subspace Clustering of High Dimensional Spatial Data with Noises
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    Chapter 7 Constraint-Based Graph Clustering through Node Sequencing and Partitioning
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    Chapter 8 Mining Expressive Process Models by Clustering Workflow Traces
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    Chapter 9 CMTreeMiner: Mining Both Closed and Maximal Frequent Subtrees
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    Chapter 10 Secure Association Rule Sharing
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    Chapter 11 Self-Similar Mining of Time Association Rules
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    Chapter 12 ParaDualMiner: An Efficient Parallel Implementation of the DualMiner Algorithm
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    Chapter 13 A Novel Distributed Collaborative Filtering Algorithm and Its Implementation on P2P Overlay Network
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    Chapter 14 An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams
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    Chapter 15 Blind Data Linkage Using n-gram Similarity Comparisons
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    Chapter 16 Condensed Representation of Emerging Patterns
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    Chapter 17 Discovery of Maximally Frequent Tag Tree Patterns with Contractible Variables from Semistructured Documents
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    Chapter 18 Advances in Knowledge Discovery and Data Mining
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    Chapter 19 FP-Bonsai: The Art of Growing and Pruning Small FP-Trees
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    Chapter 20 Mining Negative Rules Using GRD
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    Chapter 21 Applying Association Rules for Interesting Recommendations Using Rule Templates
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    Chapter 22 Feature Extraction and Classification System for Nonlinear and Online Data
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    Chapter 23 A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index
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    Chapter 24 DRC-BK: Mining Classification Rules with Help of SVM
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    Chapter 25 A New Data Mining Method Using Organizational Coevolutionary Mechanism
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    Chapter 26 Noise Tolerant Classification by Chi Emerging Patterns
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    Chapter 27 The Application of Emerging Patterns for Improving the Quality of Rare-Class Classification
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    Chapter 28 Finding Negative Event-Oriented Patterns in Long Temporal Sequences
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    Chapter 29 OBE: Outlier by Example
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    Chapter 30 Temporal Sequence Associations for Rare Events
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    Chapter 31 Summarization of Spacecraft Telemetry Data by Extracting Significant Temporal Patterns
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    Chapter 32 An Extended Negative Selection Algorithm for Anomaly Detection
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    Chapter 33 Adaptive Clustering for Network Intrusion Detection
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    Chapter 34 Ensembling MML Causal Discovery
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    Chapter 35 Logistic Regression and Boosting for Labeled Bags of Instances
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    Chapter 36 Fast and Light Boosting for Adaptive Mining of Data Streams
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    Chapter 37 Compact Dual Ensembles for Active Learning
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    Chapter 38 On the Size of Training Set and the Benefit from Ensemble
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    Chapter 39 Identifying Markov Blankets Using Lasso Estimation
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    Chapter 40 Selective Augmented Bayesian Network Classifiers Based on Rough Set Theory
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    Chapter 41 Using Self-Consistent Naive-Bayes to Detect Masquerades
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    Chapter 42 DB-Subdue: Database Approach to Graph Mining
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    Chapter 43 Finding Frequent Structural Features among Words in Tree-Structured Documents
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    Chapter 44 Exploring Potential of Leave-One-Out Estimator for Calibration of SVM in Text Mining
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    Chapter 45 Classifying Text Streams in the Presence of Concept Drifts
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    Chapter 46 Using Cluster-Based Sampling to Select Initial Training Set for Active Learning in Text Classification
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    Chapter 47 Spectral Analysis of Text Collection for Similarity-Based Clustering
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    Chapter 48 Clustering Multi-represented Objects with Noise
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    Chapter 49 Providing Diversity in K-Nearest Neighbor Query Results
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    Chapter 50 Cluster Structure of K-means Clustering via Principal Component Analysis
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    Chapter 51 Combining Clustering with Moving Sequential Pattern Mining: A Novel and Efficient Technique
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    Chapter 52 An Alternative Methodology for Mining Seasonal Pattern Using Self-Organizing Map
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    Chapter 53 ISM: Item Selection for Marketing with Cross-Selling Considerations
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    Chapter 54 Efficient Pattern-Growth Methods for Frequent Tree Pattern Mining
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    Chapter 55 Mining Association Rules from Structural Deltas of Historical XML Documents
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    Chapter 56 Data Mining Proxy: Serving Large Number of Users for Efficient Frequent Itemset Mining
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    Chapter 57 Formal Approach and Automated Tool for Translating ER Schemata into OWL Ontologies
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    Chapter 58 Separating Structure from Interestingness
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    Chapter 59 Exploiting Recurring Usage Patterns to Enhance Filesystem and Memory Subsystem Performance
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    Chapter 60 Automatic Text Extraction for Content-Based Image Indexing
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    Chapter 61 Peculiarity Oriented Analysis in Multi-people Tracking Images
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    Chapter 62 AutoSplit: Fast and Scalable Discovery of Hidden Variables in Stream and Multimedia Databases
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    Chapter 63 Semantic Sequence Kin: A Method of Document Copy Detection
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    Chapter 64 Extracting Citation Metadata from Online Publication Lists Using BLAST
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    Chapter 65 Mining of Web-Page Visiting Patterns with Continuous-Time Markov Models
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    Chapter 66 Discovering Ordered Tree Patterns from XML Queries
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    Chapter 67 Predicting Web Requests Efficiently Using a Probability Model
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    Chapter 68 CCMine: Efficient Mining of Confidence-Closed Correlated Patterns
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    Chapter 69 A Conditional Probability Distribution-Based Dissimilarity Measure for Categorial Data
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    Chapter 70 Learning Hidden Markov Model Topology Based on KL Divergence for Information Extraction
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    Chapter 71 A Non-parametric Wavelet Feature Extractor for Time Series Classification
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    Chapter 72 Rules Discovery from Cross-Sectional Short-Length Time Series
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    Chapter 73 Constraint-Based Mining of Formal Concepts in Transactional Data
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    Chapter 74 Towards Optimizing Conjunctive Inductive Queries
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    Chapter 75 Febrl – A Parallel Open Source Data Linkage System
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    Chapter 76 A General Coding Method for Error-Correcting Output Codes
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    Chapter 77 Discovering Partial Periodic Patterns in Discrete Data Sequences
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    Chapter 78 Conceptual Mining of Large Administrative Health Data
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    Chapter 79 A Semi-automatic System for Tagging Specialized Corpora
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    Chapter 80 A Tree-Based Approach to the Discovery of Diagnostic Biomarkers for Ovarian Cancer
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    Chapter 81 A Novel Parameter-Less Clustering Method for Mining Gene Expression Data
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    Chapter 82 Extracting and Explaining Biological Knowledge in Microarray Data
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    Chapter 83 Further Applications of a Particle Visualization Framework
Attention for Chapter 44: Exploring Potential of Leave-One-Out Estimator for Calibration of SVM in Text Mining
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Chapter title
Exploring Potential of Leave-One-Out Estimator for Calibration of SVM in Text Mining
Chapter number 44
Book title
Advances in Knowledge Discovery and Data Mining
Published by
Springer, Berlin, Heidelberg, May 2004
DOI 10.1007/978-3-540-24775-3_44
Book ISBNs
978-3-54-022064-0, 978-3-54-024775-3
Authors

Adam Kowalczyk, Bhavani Raskutti, Herman Ferrá

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 %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Researcher 1 20%
Unknown 3 60%
Readers by discipline Count As %
Computer Science 1 20%
Agricultural and Biological Sciences 1 20%
Psychology 1 20%
Unknown 2 40%