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Point-of-interest recommendation in location-based social networks

Author: Shenglin Zhao; Michael R Lyu; Irwin King
Publisher: Singapore : Springer, 2018.
Series: SpringerBriefs in computer science.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Zhao, Shenglin.
Point-of-interest recommendation in location-based social networks.
Singapore : Springer, 2018
(OCoLC)1038397567
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Shenglin Zhao; Michael R Lyu; Irwin King
ISBN: 9789811313493 9811313490 9811313482 9789811313486
OCLC Number: 1044746339
Description: 1 online resource.
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.
Series Title: SpringerBriefs in computer science.
Responsibility: Shenglin Zhao, Michael R. Lyu, Irwin King.

Abstract:

This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Lastly, the book discusses future research directions in this area.This book is  Read more...

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