Advances in Knowledge Discovery and Data Mining

Table of Contents

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   Book Overview
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   Chapter 1 Classifier Risk Estimation Under Limited Labeling Resources
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   Chapter 2 Social Stream Classification with Emerging New Labels
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   Chapter 3 Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules
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   Chapter 4 Modeling Label Interactions in Multi-label Classification: A Multi-structure SVM Perspective
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   Chapter 5 Sentiment Classification Using Neural Networks with Sentiment Centroids
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   Chapter 6 Random Pairwise Shapelets Forest
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   Chapter 7 A Locally Adaptive Multi-Label k -Nearest Neighbor Algorithm
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   Chapter 8 Classification with Reject Option Using Conformal Prediction
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    Chapter 9 Target Learning: A Novel Framework to Mine Significant Dependencies for Unlabeled Data
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    Chapter 10 Automatic Chinese Reading Comprehension Grading by LSTM with Knowledge Adaptation
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    Chapter 11 Data Mining with Algorithmic Transparency
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    Chapter 12 Cost-Sensitive Reference Pair Encoding for Multi-Label Learning
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    Chapter 13 Fuzzy Integral Optimization with Deep Q-Network for EEG-Based Intention Recognition
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    Chapter 14 Heterogeneous Domain Adaptation Based on Class Decomposition Schemes
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    Chapter 15 A Deep Neural Spoiler Detection Model Using a Genre-Aware Attention Mechanism
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    Chapter 16 Robust Semi-Supervised Learning on Multiple Networks with Noise
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    Chapter 17 $$\varepsilon $$ ε -Distance Weighted Support Vector Regression
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    Chapter 18 Corrosion Prediction on Sewer Networks with Sparse Monitoring Sites: A Case Study
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    Chapter 19 CAPED: Context-Aware Powerlet-Based Energy Disaggregation
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    Chapter 20 Rolling Forecasting Forward by Boosting Heterogeneous Kernels
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    Chapter 21 IDLP: A Novel Label Propagation Framework for Disease Gene Prioritization
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    Chapter 22 Deep Learning for Forecasting Stock Returns in the Cross-Section
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    Chapter 23 Vine Copula-Based Asymmetry and Tail Dependence Modeling
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    Chapter 24 Detecting Forged Alcohol Non-invasively Through Vibrational Spectroscopy and Machine Learning
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    Chapter 25 Research and Application of Mapping Relationship Based on Learning Attention Mechanism
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    Chapter 26 Human Identification via Unsupervised Feature Learning from UWB Radar Data
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    Chapter 27 Prescriptive Analytics Through Constrained Bayesian Optimization
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    Chapter 28 Neighborhood Constraint Matrix Completion for Drug-Target Interaction Prediction
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    Chapter 29 Detecting Hypopnea and Obstructive Apnea Events Using Convolutional Neural Networks on Wavelet Spectrograms of Nasal Airflow
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    Chapter 30 Deep Ensemble Classifiers and Peer Effects Analysis for Churn Forecasting in Retail Banking
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    Chapter 31 GBTM: Graph Based Troubleshooting Method for Handling Customer Cases Using Storage System Log
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    Chapter 32 Fusion of Modern and Tradition: A Multi-stage-Based Deep Network Approach for Head Detection
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    Chapter 33 Learning Treatment Regimens from Electronic Medical Records
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    Chapter 34 Mining POI Alias from Microblog Conversations
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    Chapter 35 DyPerm: Maximizing Permanence for Dynamic Community Detection
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    Chapter 36 Mining User Behavioral Rules from Smartphone Data Through Association Analysis
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    Chapter 37 A Context-Aware Evaluation Method of Driving Behavior
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    Chapter 38 Measurement of Users’ Experience on Online Platforms from Their Behavior Logs
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    Chapter 39 Mining Human Periodic Behaviors Using Mobility Intention and Relative Entropy
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    Chapter 40 Context-Uncertainty-Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning
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    Chapter 41 Learning Product Embedding from Multi-relational User Behavior
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    Chapter 42 Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure
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    Chapter 43 Visual Relation Extraction via Multi-modal Translation Embedding Based Model
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    Chapter 44 Sub-trajectory- and Trajectory-Neighbor-based Outlier Detection over Trajectory Streams
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    Chapter 45 An Unsupervised Boosting Strategy for Outlier Detection Ensembles
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    Chapter 46 DeepAD: A Generic Framework Based on Deep Learning for Time Series Anomaly Detection
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    Chapter 47 Anomaly Detection Technique Robust to Units and Scales of Measurement
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    Chapter 48 Automated Explanations of User-Expected Trends for Aggregate Queries
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    Chapter 49 Social Spammer Detection: A Multi-Relational Embedding Approach
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    Chapter 50 Learning to Rank Items of Minimal Reviews Using Weak Supervision
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    Chapter 51 Multimodal Mixture Density Boosting Network for Personality Mining
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    Chapter 52 Identifying Singleton Spammers via Spammer Group Detection
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    Chapter 53 Adaptive Attention Network for Review Sentiment Classification
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    Chapter 54 Cross-Domain Sentiment Classification via a Bifurcated-LSTM