Advances in Knowledge Discovery and Data Mining

Table of Contents

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   Book Overview
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   Chapter 1 Discovering Local Subgroups, with an Application to Fraud Detection
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   Chapter 2 PUF-Tree: A Compact Tree Structure for Frequent Pattern Mining of Uncertain Data
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   Chapter 3 Frequent Pattern Mining in Attributed Trees
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   Chapter 4 Mining Frequent Patterns from Human Interactions in Meetings Using Directed Acyclic Graphs
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   Chapter 5 ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences
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   Chapter 6 Efficient Mining of Contrast Patterns on Large Scale Imbalanced Real-Life Data
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   Chapter 7 Online Cross-Lingual PLSI for Evolutionary Theme Patterns Analysis
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   Chapter 8 F-Trail: Finding Patterns in Taxi Trajectories
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    Chapter 9 Mining Appliance Usage Patterns in Smart Home Environment
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    Chapter 10 Computational Models of Stress in Reading Using Physiological and Physical Sensor Data
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    Chapter 11 Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine
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    Chapter 12 MassBayes: A New Generative Classifier with Multi-dimensional Likelihood Estimation
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    Chapter 13 Fast and Effective Single Pass Bayesian Learning
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    Chapter 14 Sparse Reductions for Fixed-Size Least Squares Support Vector Machines on Large Scale Data
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    Chapter 15 Discovery of Regional Co-location Patterns with k-Nearest Neighbor Graph
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    Chapter 16 Spectral Decomposition for Optimal Graph Index Prediction
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    Chapter 17 Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model
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    Chapter 18 Node Classification in Social Network via a Factor Graph Model
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    Chapter 19 Advances in Knowledge Discovery and Data Mining
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    Chapter 20 Mining Interesting Itemsets in Graph Datasets
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    Chapter 21 Robust Synchronization-Based Graph Clustering
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    Chapter 22 Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors
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    Chapter 23 Exploiting Temporal Information in a Two-Stage Classification Framework for Content-Based Depression Detection
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    Chapter 24 EEG-Based Person Verification Using Multi-Sphere SVDD and UBM
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    Chapter 25 Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments Based on Self-adaptive Mixture Copula
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    Chapter 26 Mining Representative Movement Patterns through Compression
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    Chapter 27 NARGES: Prediction Model for Informed Routing in a Communications Network
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    Chapter 28 Mining Usage Traces of Mobile Apps for Dynamic Preference Prediction
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    Chapter 29 Leveraging Hybrid Citation Context for Impact Summarization
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    Chapter 30 Optimal Allocation of High Dimensional Assets through Canonical Vines
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    Chapter 31 Inducing Context Gazetteers from Encyclopedic Databases for Named Entity Recognition
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    Chapter 32 An Optimization Method for Proportionally Diversifying Search Results
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    Chapter 33 Joint Naïve Bayes and LDA for Unsupervised Sentiment Analysis
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    Chapter 34 An Unsupervised Learning Model to Perform Side Channel Attack
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    Chapter 35 Decisive Supervised Learning
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    Chapter 36 Learning Overlap Optimization for Domain Decomposition Methods
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    Chapter 37 CLUEKR : CLUstering Based Efficient kNN Regression
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    Chapter 38 AREM: A Novel Associative Regression Model Based on EM Algorithm
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    Chapter 39 One-Class Transfer Learning with Uncertain Data
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    Chapter 40 Time Series Forecasting Using Distribution Enhanced Linear Regression
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    Chapter 41 Twin Bridge Transfer Learning for Sparse Collaborative Filtering
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    Chapter 42 Dimensionality Reduction with Dimension Selection
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    Chapter 43 Multi-View Visual Classification via a Mixed-Norm Regularizer
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    Chapter 44 Mining Specific Features for Acquiring User Information Needs
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    Chapter 45 Ensemble-Based Wrapper Methods for Feature Selection and Class Imbalance Learning
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    Chapter 46 Advances in Knowledge Discovery and Data Mining
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    Chapter 47 Multiplex Topic Models
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    Chapter 48 Integrating Clustering and Ranking on Hybrid Heterogeneous Information Network
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    Chapter 49 Learning from Multiple Observers with Unknown Expertise