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BL
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| Record Number
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889881
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| Main Entry
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Zhao, Shenglin
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| Title & Author
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Point-of-interest recommendation in location-based social networks /\ Shenglin Zhao, Michael R. Lyu, Irwin King.
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| Publication Statement
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Singapore :: Springer,, 2018.
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| Series Statement
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SpringerBriefs in computer science
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| Page. NO
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1 online resource
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| ISBN
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9789811313486
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: 9789811313493
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: 9811313482
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: 9811313490
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9789811313486
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9811313482
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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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.
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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.
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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.
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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.
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| Abstract
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This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Starting with a review of the advances in this area, the book then analyzes user mobility in LBSNs from geographical and temporal perspectives. Further, it demonstrates how to build a state-of-the-art POI recommendation system by incorporating the user behavior analysis. Lastly, the book discusses future research directions in this area. This book is intended for professionals involved in POI recommendation and graduate students working on problems related to location-based services. It is assumed that readers have a basic knowledge of mathematics, as well as some background in recommendation systems.
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| Subject
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Location-based services-- Social aspects.
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| Subject
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Social media.
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| Subject
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PSYCHOLOGY-- Social Psychology.
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| Subject
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Social media.
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| Dewey Classification
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302.231
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| LC Classification
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HM742
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| Added Entry
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King, Irwin
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Lyu, Michael R.
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