Advances in Knowledge Discovery and Data Mining

Table of Contents

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   Book Overview
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   Chapter 1 CTROF: A Collaborative Tweet Ranking Framework for Online Personalized Recommendation
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   Chapter 2 Advances in Knowledge Discovery and Data Mining
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   Chapter 3 Dynamic Circle Recommendation: A Probabilistic Model
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   Chapter 4 HOSLIM: Higher-Order Sparse LInear Method for Top- N Recommender Systems
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   Chapter 5 Mining GPS Data for Trajectory Recommendation
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   Chapter 6 Advances in Knowledge Discovery and Data Mining
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   Chapter 7 Advances in Knowledge Discovery and Data Mining
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   Chapter 8 Highly Scalable Attribute Selection for Averaged One-Dependence Estimators
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    Chapter 9 Advances in Knowledge Discovery and Data Mining
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    Chapter 10 Advances in Knowledge Discovery and Data Mining
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    Chapter 11 Machine Learning Approaches for Interactive Verification
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    Chapter 12 Positional Translation Language Model for Ad-Hoc Information Retrieval
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    Chapter 13 Topic Modeling Using Collapsed Typed Dependency Relations
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    Chapter 14 Advances in Knowledge Discovery and Data Mining
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    Chapter 15 Crime Forecasting Using Spatio-temporal Pattern with Ensemble Learning
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    Chapter 16 NLPMM: A Next Location Predictor with Markov Modeling
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    Chapter 17 Beyond Poisson: Modeling Inter-Arrival Time of Requests in a Datacenter
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    Chapter 18 Brownian Bridge Model for High Resolution Location Predictions
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    Chapter 19 Mining Correlation Patterns among Appliances in Smart Home Environment
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    Chapter 20 Advances in Knowledge Discovery and Data Mining
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    Chapter 21 Extensions to Quantile Regression Forests for Very High-Dimensional Data
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    Chapter 22 Inducing Controlled Error over Variable Length Ranked Lists
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    Chapter 23 Advances in Knowledge Discovery and Data Mining
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    Chapter 24 A Graphical Model for Collective Behavior Learning Using Minority Games
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    Chapter 25 Finding Better Topics: Features, Priors and Constraints
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    Chapter 26 Finding Well-Clusterable Subspaces for High Dimensional Data
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    Chapter 27 Determine Optimal Number of Clusters with an Elitist Evolutionary Approach
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    Chapter 28 Crowdordering
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    Chapter 29 Document Clustering with an Augmented Nonnegative Matrix Factorization Model
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    Chapter 30 Visualization of PICO Elements for Information Needs Clarification and Query Refinement
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    Chapter 31 Mining Biomedical Literature and Ontologies for Drug Repositioning Discovery
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    Chapter 32 Inferring Metapopulation Based Disease Transmission Networks
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    Chapter 33 A Novel Framework to Improve siRNA Efficacy Prediction
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    Chapter 34 Advances in Knowledge Discovery and Data Mining
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    Chapter 35 Recurring and Novel Class Detection in Concept-Drifting Data Streams Using Class-Based Ensemble
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    Chapter 36 Detecting Changes in Rare Patterns from Data Streams
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    Chapter 37 Noise-Tolerant Approximate Blocking for Dynamic Real-Time Entity Resolution
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    Chapter 38 A Relevance Weighted Ensemble Model for Anomaly Detection in Switching Data Streams
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    Chapter 39 MultiAspectSpotting : Spotting Anomalous Behavior within Count Data Using Tensor
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    Chapter 40 Outlier Detection Based on Leave-One-Out Density Using Binary Decision Diagrams
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    Chapter 41 Rare Category Detection on O ( dN ) Time Complexity
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    Chapter 42 Improving iForest with Relative Mass
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    Chapter 43 Domain Transfer via Multiple Sources Regularization
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    Chapter 44 Mining Diversified Shared Decision Tree Sets for Discovering Cross Domain Similarities
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    Chapter 45 Semi-supervised Clustering on Heterogeneous Information Networks
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    Chapter 46 A Content-Based Matrix Factorization Model for Recipe Recommendation
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    Chapter 47 Unsupervised Analysis of Web Page Semantic Structures by Hierarchical Bayesian Modeling
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    Chapter 48 For User-Driven Software Evolution: Requirements Elicitation Derived from Mining Online Reviews
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    Chapter 49 Automatic Fake Followers Detection in Chinese Micro-blogging System
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    Chapter 50 Constrained-hLDA for Topic Discovery in Chinese Microblogs