Graph Mining: Laws, Tools, and Case Studies (Paperback)

Deepayan Chakrabarti, Christos Faloutsos

  • 出版商: Morgan & Claypool
  • 出版日期: 2012-10-01
  • 售價: $1,740
  • 貴賓價: 9.5$1,653
  • 語言: 英文
  • 頁數: 208
  • 裝訂: Paperback
  • ISBN: 1608451151
  • ISBN-13: 9781608451159
  • 相關分類: Amazon Web Services
  • 海外代購書籍(需單獨結帳)

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商品描述

What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others.

In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints.

Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

商品描述(中文翻譯)

網頁是什麼樣子?我們如何在社交網絡中找到模式、社群和異常值?網絡中最核心的節點是哪些?這些問題是本研究的動機。網絡和圖形出現在許多不同的場景中,例如社交網絡、計算機通信網絡(入侵檢測、流量管理)、生物學中的蛋白質相互作用網絡、文本檢索中的文檔-文本二分圖、金融欺詐檢測中的人-帳戶圖等等。

在這項工作中,首先我們列出了一些真實圖形常見的令人驚訝的模式。然後我們提供了一個詳細的生成器列表,試圖模擬這些模式。生成器很重要,因為它們可以幫助處理「如果」情景、推斷和匿名化。然後我們提供了一個強大的圖形分析工具列表,特別是光譜方法(奇異值分解(SVD))、張量和像著名的「PageRank」算法和「HITS」算法這樣的案例研究,用於排名網絡搜索結果。最後,我們總結了來自社會學等相關領域的工具和觀察,提供了互補的觀點。

目錄:引言 / 靜態圖形中的模式 / 演化圖形中的模式 / 加權圖形中的模式 / 討論:特定圖形的結構 / 討論:冪律和偏差 / 模式摘要 / 圖形生成器 / 偏好連接和變體 / 結合地理信息 / RMat / 通過克羅內克乘法生成圖形 / 摘要和實踐指南 / SVD、隨機遊走和張量 / 張量 / 社群檢測 / 影響/病毒傳播和免疫 / 案例研究 / 社交網絡 / 其他相關工作 / 結論