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Aggarwal / Wang

Managing and Mining Graph Data

Medium: Buch
ISBN: 978-1-4614-2560-1
Verlag: Humana
Erscheinungstermin: 06.04.2012
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9781461425601
  • Medium: Buch
  • ISBN: 978-1-4614-2560-1
  • Verlag: Humana
  • Erscheinungstermin: 06.04.2012
  • Sprache(n): Englisch
  • Auflage: 2010
  • Serie: Advances in Database Systems
  • Produktform: Kartoniert, Paperback
  • Gewicht: 949 g
  • Seiten: 600
  • Format (B x H x T): 155 x 235 x 34 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

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.