Managing and Mining Graph Data

• Corporate Author: SpringerLink (Online service)
• Other Authors: Aggarwal, Charu C. (Editor), Wang, Haixun (Editor)
• Format: Electronic eBook
• Language: English
• Published: Boston, MA : Springer US, 2010.
• Series: Advances in Database Systems, 40
• Subjects: Computer science.; Database management.; Data mining.; Information storage and retrieval.; Computer graphics.; Application software.; Computer Science.; Data Mining and Knowledge Discovery.; Database Management.; Computer Applications.; Computer Graphics.; Information Storage and Retrieval.; Information Systems Applications (incl. Internet).

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...

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.