Managing and Mining Graph Data

By: Charu C. Aggarwal (Editor), Haixun Wang (Editor)

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Hardcover | 19 February 2010

At a Glance

Hardcover
636 Pages

Dimensions(cm)
24.2 x 16.4 x 3.9

Hardcover

$329.00

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Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing.

Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.

Industry Reviews

From the reviews:

"This book provides a survey of some recent advances in graph mining. It contains chapters on graph languages, indexing, clustering, pattern mining, keyword search, and pattern matching. ... The book is targeted at advanced undergraduate or graduate students, faculty members, and researchers from both industry and academia. ... I highly recommend this book to someone who is starting to explore the field of graph mining or wants to delve deeper into this exciting field." (Dimitrios Katsaros, ACM Computing Reviews, December, 2010)

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