<p><P><EM>Managing and Mining Graph Data</EM> 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.
Managing and Mining Graph Data
โ Scribed by Charu C. Aggarwal, Haixun Wang (auth.), Charu C. Aggarwal, Haixun Wang (eds.)
- Publisher
- Springer US
- Year
- 2010
- Tongue
- English
- Leaves
- 620
- Series
- Advances in database systems 40
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Subjects
Database Management; Data Mining and Knowledge Discovery; Computer Graphics; Information Storage and Retrieval; Information Systems Applications (incl.Internet)
๐ SIMILAR VOLUMES
<p><P><EM>Managing and Mining Graph Data</EM> 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.
<p><P><EM>Managing and Mining Graph Data</EM> 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.
This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book youโll be able to represent data as graphs, extract patt
This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you'll be able to represent data as graphs, extract patt