Point-of-interest recommendation in location-based social networks /
General Material Designation
[Book]
First Statement of Responsibility
Shenglin Zhao, Michael R. Lyu, Irwin King.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
SERIES
Series Title
SpringerBriefs in computer science
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
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.
Text of Note
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.
Text of Note
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.
Text of Note
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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SUMMARY OR ABSTRACT
Text of Note
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.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
00024965
Stock Number
9789811313486
OTHER EDITION IN ANOTHER MEDIUM
Title
Point-of-interest recommendation in location-based social networks.