Overview

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.

Full Product Details

Author:   Charu C. Aggarwal ,  Haixun Wang
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Previously published in hardcover
Volume:   40
Dimensions:   Width: 15.50cm , Height: 3.20cm , Length: 23.50cm
Weight:   0.961kg
ISBN:  

9781461425601

ISBN 10:   1461425603
Pages:   600
Publication Date:   06 April 2012
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

An Introduction to Graph Data.- Graph Data Management and Mining: A Survey of Algorithms and Applications.- Graph Mining: Laws and Generators.- Query Language and Access Methods for Graph Databases.- Graph Indexing.- Graph Reachability Queries: A Survey.- Exact and Inexact Graph Matching: Methodology and Applications.- A Survey of Algorithms for Keyword Search on Graph Data.- A Survey of Clustering Algorithms for Graph Data.- A Survey of Algorithms for Dense Subgraph Discovery.- Graph Classification.- Mining Graph Patterns.- A Survey on Streaming Algorithms for Massive Graphs.- A Survey of Privacy-Preservation of Graphs and Social Networks.- A Survey of Graph Mining for Web Applications.- Graph Mining Applications to Social Network Analysis.- Software-Bug Localization with Graph Mining.- A Survey of Graph Mining Techniques for Biological Datasets.- Trends in Chemical Graph Data Mining.

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)

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)

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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