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Table of Contents
Intro; Preface; Contents; 1 Introduction; 1.1 Overview; 1.2 Backgrounds; 1.2.1 Problem Description; 1.2.2 User Behavior Analysis; 1.2.3 Methodologies; 1.3 Book Organization; References; 2 Understanding Human Mobility from Geographical Perspective; 2.1 Introduction; 2.2 Related Work; 2.3 Model; 2.3.1 Gaussian Mixture Model; 2.3.2 Genetic Algorithm Based Gaussian Mixture Model; 2.4 Experiment; 2.4.1 Setup and Metrics; 2.4.2 Dataset; 2.4.3 Results; 2.5 Conclusion; References; 3 Understanding Human Mobility from Temporal Perspective; 3.1 Introduction; 3.2 Related Work; 3.3 Preliminaries
3.3.1 Empirical Data Analysis3.3.2 Time Labeling Scheme; 3.4 Method; 3.4.1 Aggregated Temporal Tensor Factorization Model; 3.4.2 Learning; 3.4.3 Model Discussion; 3.5 Experiment; 3.5.1 Data Description and Experimental Setting; 3.5.2 Performance Metrics; 3.5.3 Baselines; 3.5.4 Experimental Results; 3.6 Conclusion; References; 4 Geo-Teaser: Geo-Temporal Sequential Embedding Rank for POI Recommendation; 4.1 Introduction; 4.2 Related Work; 4.3 Data Description and Analysis; 4.3.1 Data Description; 4.3.2 Empirical Analysis; 4.4 Method; 4.4.1 Temporal POI Embedding
4.4.2 Geographically Hierarchical Pairwise Ranking4.4.3 Geo-Teaser Model; 4.4.4 Learning; 4.5 Experimental Evaluation; 4.5.1 Experimental Setting; 4.5.2 Performance Metrics; 4.5.3 Model Comparison; 4.5.4 Experimental Results; 4.6 Conclusion; References; 5 STELLAR: Spatial-Temporal Latent Ranking Model for Successive POI Recommendation; 5.1 Introduction; 5.2 Related Work; 5.3 Data Description and Successive Check-in Analysis; 5.3.1 Data Description; 5.3.2 Successive Check-in Analysis; 5.4 STELLAR Model; 5.4.1 Time Indexing Scheme; 5.4.2 Model Formulation; 5.4.3 Model Inference and Learning
5.5 Experiment5.5.1 Experimental Setting; 5.5.2 Comparison of Methods; 5.5.3 Experimental Results; 5.5.4 Discussion of Time Indexing Scheme; 5.5.5 Parameter Effect; 5.6 Conclusion; References; 6 Conclusion and Future Work; 6.1 Conclusion; 6.2 Future Work; 6.2.1 Ranking-Based Model; 6.2.2 Online Recommendation; 6.2.3 Deep Learning Based Recommendation; References; Index
3.3.1 Empirical Data Analysis3.3.2 Time Labeling Scheme; 3.4 Method; 3.4.1 Aggregated Temporal Tensor Factorization Model; 3.4.2 Learning; 3.4.3 Model Discussion; 3.5 Experiment; 3.5.1 Data Description and Experimental Setting; 3.5.2 Performance Metrics; 3.5.3 Baselines; 3.5.4 Experimental Results; 3.6 Conclusion; References; 4 Geo-Teaser: Geo-Temporal Sequential Embedding Rank for POI Recommendation; 4.1 Introduction; 4.2 Related Work; 4.3 Data Description and Analysis; 4.3.1 Data Description; 4.3.2 Empirical Analysis; 4.4 Method; 4.4.1 Temporal POI Embedding
4.4.2 Geographically Hierarchical Pairwise Ranking4.4.3 Geo-Teaser Model; 4.4.4 Learning; 4.5 Experimental Evaluation; 4.5.1 Experimental Setting; 4.5.2 Performance Metrics; 4.5.3 Model Comparison; 4.5.4 Experimental Results; 4.6 Conclusion; References; 5 STELLAR: Spatial-Temporal Latent Ranking Model for Successive POI Recommendation; 5.1 Introduction; 5.2 Related Work; 5.3 Data Description and Successive Check-in Analysis; 5.3.1 Data Description; 5.3.2 Successive Check-in Analysis; 5.4 STELLAR Model; 5.4.1 Time Indexing Scheme; 5.4.2 Model Formulation; 5.4.3 Model Inference and Learning
5.5 Experiment5.5.1 Experimental Setting; 5.5.2 Comparison of Methods; 5.5.3 Experimental Results; 5.5.4 Discussion of Time Indexing Scheme; 5.5.5 Parameter Effect; 5.6 Conclusion; References; 6 Conclusion and Future Work; 6.1 Conclusion; 6.2 Future Work; 6.2.1 Ranking-Based Model; 6.2.2 Online Recommendation; 6.2.3 Deep Learning Based Recommendation; References; Index