| 书目名称 | Social Network-Based Recommender Systems | | 编辑 | Daniel Schall | | 视频video | | | 概述 | Introduces novel concepts and techniques about the formation of social networks and each chapter concludes with an analysis and summary.Provides real world datasets from GitHub, Facebook, Twitter, Goo | | 图书封面 |  | | 描述 | This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ‘social brokers’ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will alsofind this books useful as a secondary text. | | 出版日期 | Book 2015 | | 关键词 | Follow recommendation; Formation patterns; GitHub; Graph patterns; Link prediction; Multi-criteria rankin | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-22735-1 | | isbn_softcover | 978-3-319-37229-7 | | isbn_ebook | 978-3-319-22735-1 | | copyright | Springer International Publishing Switzerland 2015 |
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发表于 2025-3-21 18:30:31
