Managing and Mining Graph Data

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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Aggarwal, Charu C. (Editor ), Wang, Haixun (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Advances in Database Systems ; 40
Temas:
Data mining.
Database management.
Application software.
Computer graphics.
Information storage and retrieval systems.
Data Mining and Knowledge Discovery.
Database Management.
Computer and Information Systems Applications.
Computer Graphics.
Information Storage and Retrieval.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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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