Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)
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Table of contents (9 chapters)
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Front Matter
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Basic Definitions and Concepts
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Front Matter
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Recommendation Algorithms in LBSNs
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Front Matter
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Implementing a Real-World LBSN
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Front Matter
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Keywords
About this book
Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs.
The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of these recommender systems. Part 3 provides a step-by-step case study on the technical aspects of deploying and evaluating a real-world LBSN, which provides location, activity and friend recommendations. The material covered in the book is intended for graduate students, teachers, researchers, and practitioners in the areas of web data mining, information retrieval, and machine learning.
Authors and Affiliations
Bibliographic Information
Book Title: Recommender Systems for Location-based Social Networks
Authors: Panagiotis Symeonidis, Dimitrios Ntempos, Yannis Manolopoulos
Series Title: SpringerBriefs in Electrical and Computer Engineering
DOI: https://doi.org/10.1007/978-1-4939-0286-6
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2014
Softcover ISBN: 978-1-4939-0285-9Published: 08 February 2014
eBook ISBN: 978-1-4939-0286-6Published: 08 February 2014
Series ISSN: 2191-8112
Series E-ISSN: 2191-8120
Edition Number: 1
Number of Pages: V, 108
Number of Illustrations: 8 b/w illustrations, 33 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Artificial Intelligence, Information Systems Applications (incl. Internet)