Overview
- The first book to analyze the new characteristics of social media in the era of mobile internet
- Covers all emerging tasks and cutting-edge techniques for Spatio-Temporal Recommendation in Social Media
- Addresses seminal research approaches and technologies from a practical standpoint
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (5 chapters)
Keywords
About this book
This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users’ behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users’ behaviors, user interest drift over geographical regions, data sparsity and cold start. Based on these well designed user models, the book develops effective multi-dimensional index structures such as Metric-Tree, and proposes efficient top-k retrieval algorithms to accelerate the process of online recommendation and support real-time recommendation. In addition, it offers methodologies and techniques for evaluating both the effectiveness and efficiency of spatio-temporal recommendation systems in social media. The book will appeal to a broad readership, from researchers and developers to undergraduate and graduate students.
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Authors and Affiliations
About the authors
Prof. Bin Cui is a faculty member at the School of EECS and Vice Director of the Institute of Network Computing and Information Systems, at Peking University. He obtained his BSc from Xi'an Jiaotong University (Pilot Class) in 1996, and his PhD from the National University of Singapore in 2004. From 2004 to 2006, he worked as a Research Fellow in the Singapore-MIT Alliance. His research interests include database system architectures, query and index techniques, and big data management and mining. He has served in the Technical Program Committee of various international conferences including SIGMOD, VLDB, ICDE and KDD, and as Vice PC Chair of ICDE 2011, Demo CO-Chair for ICDE 2014, and as Area Chair of VLDB 2014. He is currently on the Editorial Board of VLDB Journal, Distributed and Parallel Databases Journal, Information Systems, and Frontier of ComputerScience, and was an associate editor of IEEE Transactions on Knowledge and Data Engineering (TKDE, 2009-2013). He has received the Microsoft Young Professorship award (MSRA 2008) and the CCF Young Scientist award (2009). He is a senior member of IEEE, member of ACM and distinguished member of CCF.
Bibliographic Information
Book Title: Spatio-Temporal Recommendation in Social Media
Authors: Hongzhi Yin, Bin Cui
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-981-10-0748-4
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media Singapore 2016
Softcover ISBN: 978-981-10-0747-7Published: 25 May 2016
eBook ISBN: 978-981-10-0748-4Published: 19 May 2016
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XIII, 114
Number of Illustrations: 4 b/w illustrations, 22 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Information Storage and Retrieval, Information Systems Applications (incl. Internet), Database Management