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Social Network Data Analytics (Hardcover)
暫譯: 社交網路數據分析 (精裝版)

Charu C. Aggarwal

  • 出版商: Springer
  • 出版日期: 2011-03-17
  • 售價: $6,780
  • 貴賓價: 9.5$6,441
  • 語言: 英文
  • 頁數: 502
  • 裝訂: Hardcover
  • ISBN: 1441984615
  • ISBN-13: 9781441984616
  • 相關分類: Data Science
  • 海外代購書籍(需單獨結帳)

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商品描述

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes.

Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book.

This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

商品描述(中文翻譯)

社交網路分析應用在過去幾年中經歷了巨大的進步,部分原因是用戶在互聯網上互動的趨勢日益增加。社交網路被組織為圖形,而社交網路上的數據則以大量的數據流形式存在,這些數據流被挖掘用於各種目的。

《社交網路數據分析》涵蓋了社交網路分析領域中的一個重要利基。這本編輯書籍由該領域的知名研究者貢獻,呈現了關於社交網路數據挖掘的廣泛主題,例如社交網路的結構特性、社交網路的結構發現算法以及社交網路中的內容分析。這本書的獨特之處在於專注於互聯網情境下社交網路的數據分析方面,而不是現有書籍中普遍存在的以社會學為驅動的傳統強調,後者並未專注於在線社交網路獨特的數據密集特性。書中強調簡化內容,以便學生和從業者能夠從中受益。

本書針對高級學生和研究人員,作為計算機科學的輔助教材或參考書。數據挖掘、數據庫、資訊安全、電子商務和機器學習專業人士將會發現這本書是個有價值的資產,此外,像是ACM、IEEE和管理科學等主要協會也會受益於此書。

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