Practical Graph Mining with R (Hardcover)

Nagiza F. Samatova, William Hendrix, John Jenkins, Kanchana Padmanabhan, Arpan Chakraborty

  • 出版商: CRC
  • 出版日期: 2013-07-15
  • 售價: $3,150
  • 貴賓價: 9.5$2,993
  • 語言: 英文
  • 頁數: 495
  • 裝訂: Hardcover
  • ISBN: 143986084X
  • ISBN-13: 9781439860847
  • 相關分類: R 語言
  • 立即出貨 (庫存 < 3)

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商品描述

Discover Novel and Insightful Knowledge from Data Represented as a Graph
Practical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or clusters of nodes that share common patterns of attributes and relationships, the extraction of patterns that distinguish one category of graphs from another, and the use of those patterns to predict the category of new graphs.

 

Hands-On Application of Graph Data Mining
Each chapter in the book focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through applications using real data sets, the book demonstrates how computational techniques can help solve real-world problems. The applications covered include network intrusion detection, tumor cell diagnostics, face recognition, predictive toxicology, mining metabolic and protein-protein interaction networks, and community detection in social networks.

 

Develops Intuition through Easy-to-Follow Examples and Rigorous Mathematical Foundations
Every algorithm and example is accompanied with R code. This allows readers to see how the algorithmic techniques correspond to the process of graph data analysis and to use the graph mining techniques in practice. The text also gives a rigorous, formal explanation of the underlying mathematics of each technique.

 

Makes Graph Mining Accessible to Various Levels of Expertise
Assuming no prior knowledge of mathematics or data mining, this self-contained book is accessible to students, researchers, and practitioners of graph data mining. It is suitable as a primary textbook for graph mining or as a supplement to a standard data mining course. It can also be used as a reference for researchers in computer, information, and computational science as well as a handy guide for data analytics practitioners.

商品描述(中文翻譯)

《Practical Graph Mining with R》是一本介紹如何從以圖形表示的數據中提取有趣模式的書籍。它提供了一種「自助」的方法,涵蓋了許多基本和高級技術,用於識別圖形中的異常或經常出現的模式,發現共享屬性和關係模式的節點組或群集,提取區分一類圖形與另一類圖形的模式,並使用這些模式來預測新圖形的類別。

本書的每一章都聚焦於一個圖形挖掘任務,例如連結分析、群集分析和分類。通過使用真實數據集的應用,本書展示了計算技術如何幫助解決現實世界的問題。這些應用包括網絡入侵檢測、腫瘤細胞診斷、人臉識別、預測毒理學、挖掘代謝和蛋白質相互作用網絡,以及社交網絡中的社區檢測。

書中的每個算法和示例都附有R代碼。這使讀者能夠看到算法技術如何對應於圖形數據分析過程,並在實踐中使用圖形挖掘技術。本書還對每種技術的基礎數學進行了嚴格而正式的解釋。

本書假設讀者對數學或數據挖掘沒有先備知識,因此適用於圖形數據挖掘的學生、研究人員和從業人員。它可以作為圖形挖掘的主要教材,也可以作為標準數據挖掘課程的補充教材。同時,它還可以作為計算機、信息和計算科學研究人員的參考書,以及數據分析從業人員的實用指南。