| 书目名称 | Recommender Systems for Location-based Social Networks | | 编辑 | Panagiotis Symeonidis,Dimitrios Ntempos,Yannis Man | | 视频video | | | 概述 | Includes supplementary material: | | 丛书名称 | SpringerBriefs in Electrical and Computer Engineering | | 图书封面 |  | | 描述 | .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 an | | 出版日期 | Book 2014 | | 关键词 | Algorithms; information filtering; location-based social networks; performance; real-world case study; re | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4939-0286-6 | | isbn_softcover | 978-1-4939-0285-9 | | isbn_ebook | 978-1-4939-0286-6Series ISSN 2191-8112 Series E-ISSN 2191-8120 | | issn_series | 2191-8112 | | copyright | The Author(s) 2014 |
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发表于 2025-3-21 18:22:21
