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Social networks with rich edge semantics / Quan Zheng, David Skillicorn
(Chapman & Hall/CRC data mining and knowledge discovery series)
| データ種別 | 電子ブック |
|---|---|
| 版 | First edition |
| 出版者 | Boca Raton, FL : CRC Press, Taylor & Francis Group |
| 出版年 | [2017] |
| 本文言語 | 英語 |
| 大きさ | 1 online resource (xx, 210 pages) |
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| 資料種別 | 機械可読データファイル |
|---|---|
| 内容注記 | Cover ; Half title ; Published titles ; Title ; Copyright ; Contents ; Preface ; List of figures ; List of tables ; Glossary ; Chapter 1 introduction; 1.1 what is a social network 1.2 multiple aspects of relationships 1.3 formally representing social networks ; Chapter 2 the core model 2.1 representing networks to understand their structures 2.2 building layered models ; 2.3 summary ; Chapter 3 background; 3.1 graph theory background 3.2 spectral graph theory 3.2.1 the unnormalized graph laplacian ; 3.2.2 the normalized graph laplacians ; 3.3 spectral pipeline 3.4 spectral approaches to clustering 3.4.1 undirected spectral clustering algorithms ; 3.4.2 which laplacian clustering should be used |
| 一般注記 | "Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities, including different types of relationships, different strengths in the directions of a pair, positive and negative relationships, and relationships whose intensities change with time. For each possibility, the book shows how to model the social network using spectral embedding. It also shows how to compose the techniques so that multiple edge semantics can be modeled together, and the modeling techniques are then applied to a range of datasets. Features introduces the reader to difficulties with current social network analysis, and the need for richer representations of relationships among nodes, including accounting for intensity, direction, type, positive/negative, and changing intensities over time presents a novel mechanism to allow social networks with qualitatively different kinds of relationships to be described and analyzed includes extensions to the important technique of spectral embedding, shows that they are mathematically well motivated and proves that their results are appropriates hows how to exploit embeddings to understand structures within social networks, including subgroups, positional significance, link or edge prediction, consistency of role in different contexts, and net flow of properties through a node illustrates the use of the approach for real-world problems for online social networks, criminal and drug smuggling networks, and networks where the nodes are themselves groups suitable for researchers and students in social network research, data science, statistical learning, and related areas, this book will help to provide a deeper understanding of real-world social networks."--Provided by publisher Open Access Includes bibliographical references and index |
| 著者標目 | *Zheng, Quan Skillicorn, David. |
| 件 名 | LCSH:Electronic books BSH:Electronic books LCSH:Social networks -- Mathematical models 全ての件名で検索 LCSH:Semantic Web LCSH:Social media FREE:Internet: general works BISACSH:COMPUTERS -- Machine Theory 全ての件名で検索 BISACSH:BUSINESS & ECONOMICS -- Statistics 全ての件名で検索 FREE:Social media FREE:Semantic Web FREE:Social networks -- Mathematical models 全ての件名で検索 |
| 分 類 | DC23:302.3015118 |
| 書誌ID | ED00001391 |
| ISBN | 9781315390628 |