Managing and Mining Graph Data

Managing and Mining Graph Data edited by Charu C. Aggarwal, Haixun Wang.

Managing and Mining Graph Data is a comprehensive survey book in graph data analytics. It contains extensive surveys on important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studie...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Aggarwal, Charu C. (Editor), Wang, Haixun (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2010.
Edition:1st ed. 2010.
Series:Advances in Database Systems, 40
Springer eBook Collection.
Subjects:
Data mining.
Database management.
Application software.
Computer graphics.
Information storage and retrieval.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
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.

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