Advances in Knowledge Discovery and Data Mining

Table of Contents

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   Book Overview
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   Chapter 1 Time-Evolving Relational Classification and Ensemble Methods
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   Chapter 2 Active Learning for Hierarchical Text Classification
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   Chapter 3 TeamSkill Evolved: Mixed Classification Schemes for Team-Based Multi-player Games
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   Chapter 4 A Novel Weighted Ensemble Technique for Time Series Forecasting
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   Chapter 5 Techniques for Efficient Learning without Search
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   Chapter 6 An Aggressive Margin-Based Algorithm for Incremental Learning
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   Chapter 7 Two-View Online Learning
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   Chapter 8 A Generic Classifier-Ensemble Approach for Biomedical Named Entity Recognition
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    Chapter 9 Neighborhood Random Classification
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    Chapter 10 SRF: A Framework for the Study of Classifier Behavior under Training Set Mislabeling Noise
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    Chapter 11 Building Decision Trees for the Multi-class Imbalance Problem
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    Chapter 12 Scalable Random Forests for Massive Data
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    Chapter 13 Hybrid Random Forests: Advantages of Mixed Trees in Classifying Text Data
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    Chapter 14 Learning Tree Structure of Label Dependency for Multi-label Learning
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    Chapter 15 Multiple Instance Learning for Group Record Linkage
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    Chapter 16 Incremental Set Recommendation Based on Class Differences
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    Chapter 17 Active Learning for Cross Language Text Categorization
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    Chapter 18 Evasion Attack of Multi-class Linear Classifiers
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    Chapter 19 Foundation of Mining Class-Imbalanced Data
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    Chapter 20 Active Learning with c-Certainty
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    Chapter 21 A Term Association Translation Model for Naive Bayes Text Classification
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    Chapter 22 A Double-Ensemble Approach for Classifying Skewed Data Streams
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    Chapter 23 Generating Balanced Classifier-Independent Training Samples from Unlabeled Data
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    Chapter 24 Nyström Approximate Model Selection for LSSVM
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    Chapter 25 Exploiting Label Dependency for Hierarchical Multi-label Classification
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    Chapter 26 Diversity Analysis on Boosting Nominal Concepts
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    Chapter 27 Extreme Value Prediction for Zero-Inflated Data
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    Chapter 28 Learning to Diversify Expert Finding with Subtopics
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    Chapter 29 An Associative Classifier for Uncertain Datasets
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    Chapter 30 Neighborhood-Based Smoothing of External Cluster Validity Measures
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    Chapter 31 Sequential Entity Group Topic Model for Getting Topic Flows of Entity Groups within One Document
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    Chapter 32 Topological Comparisons of Proximity Measures
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    Chapter 33 Quad-tuple PLSA: Incorporating Entity and Its Rating in Aspect Identification
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    Chapter 34 Clustering-Based k -Anonymity
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    Chapter 35 Unsupervised Ensemble Learning for Mining Top-n Outliers
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    Chapter 36 Towards Personalized Context-Aware Recommendation by Mining Context Logs through Topic Models
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    Chapter 37 Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases
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    Chapter 38 A Vertex Similarity Probability Model for Finding Network Community Structure
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    Chapter 39 Hybrid- ε -greedy for Mobile Context-Aware Recommender System
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    Chapter 40 Advances in Knowledge Discovery and Data Mining
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    Chapter 41 Semantic Social Network Analysis with Text Corpora
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    Chapter 42 Advances in Knowledge Discovery and Data Mining
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    Chapter 43 Feature Enriched Nonparametric Bayesian Co-clustering
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    Chapter 44 Shape-Based Clustering for Time Series Data
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    Chapter 45 Privacy-Preserving EM Algorithm for Clustering on Social Network
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    Chapter 46 Named Entity Recognition and Identification for Finding the Owner of a Home Page
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    Chapter 47 Clustering and Understanding Documents via Discrimination Information Maximization
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    Chapter 48 A Semi-supervised Incremental Clustering Algorithm for Streaming Data
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    Chapter 49 Unsupervised Sparse Matrix Co-clustering for Marketing and Sales Intelligence
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    Chapter 50 Expectation-Maximization Collaborative Filtering with Explicit and Implicit Feedback