Point-Of-Interest Recommendation in Location-Based Social Networks

Michael R Lyu

ISBN 10: 9811313482 / ISBN 13: 9789811313486

Edité par Springer Nature Singapore, 2018

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - 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.

N° de réf. du vendeur 9789811313486

Détails bibliographiques

• Titre: Point-Of-Interest Recommendation in Location-Based Social Networks
• Éditeur: Springer Nature Singapore
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 9811313482
• ISBN à 13 chiffres: 9789811313486
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 233 L x 156 H x 12 P (en millimètres) 233 millimètres de largeur par 156 millimètres de hauteur par 12 millimètres de profondeur
• Poids: 191 grammes

A propos de ce titre

Synopsis

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.

À propos de l'auteur

Dr. Shenglin Zhao is currently a senior researcher at Youtu Lab in Tencent, and was recently awarded a Ph.D. by the Chinese University of Hong Kong. He is an expert in the area of recommendation systems, especially for POI recommendation. In this area, he has published several journal and conference papers, such as "Geo-Pairwise Ranking Matrix Factorization Model for Point-of-Interest Recommendation" (ICONIP 17, Best Paper Runner-up), "Geo-teaser: Geo-temporal sequential embedding rank for point-of-interest recommendation"(WWW17), and "STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation" (AAAI 16).

Dr. Michael R. Lyu is currently a Professor and the Chairman of the Department of Computer Science and Engineering at the Chinese University of Hong Kong. He was elected IEEE Fellow in 2004, AAAS Fellow in 2007, and ACM Fellow in 2015. His research interests include software engineering, dependable computing, distributed systems, cloud computing, mobile networking, big data, and machine learning. He has published over 480 refereed journal and conference papers.

Dr. Irwin King is Associate Dean (Education) at the Faculty of Engineering and a Professor at the Department of Computer Science and Engineering, the Chinese University of Hong Kong. His research interests include machine learning, social computing, web intelligence, data mining, and multimedia information processing. In these areas, he has published over 210 technical papers in various journals (JMLR, ACM TOIS, IEEE TNN, Neurocomputing, NN, IEEE BME, PR, IEEE SMC, JAMC, JASIST, IJPRAI, DSS, etc.) and conferences (NIPS, IJCAI, CIKM, SIGIR, KDD, PAKDD, ICDM, WWW, WI/IAT, WCCI, IJCNN, ICONIP, ICDAR.). In addition, he has contributed over 30 book chapters to edited volumes.