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.
Format: Paperback / softback
CONTRIBUTORS: Charu C. Aggarwal
EAN: 9781461425601
COUNTRY: United States
PAGES:
WEIGHT: 961 g
HEIGHT: 235 cm
PUBLISHED BY: Springer-Verlag New York Inc.
DATE PUBLISHED: 2012-04-06
CITY:
GENRE: COMPUTERS / Software Development & Engineering / Computer Graphics, COMPUTERS / Data Science / General, COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Analytics, COMPUTERS / System Administration / Storage & Retrieval
WIDTH: 155 cm
SPINE:
Book Themes:
Graphics programming, Databases, Data warehousing, Data mining, Information retrieval, Applied computing, Expert systems / knowledge-based systems
From the reviews:“This book provides a survey of some recent advances in graph mining. It contains chapters on graph languages, indexing, clustering, pattern mining, keyword search, and pattern matching. … The book is targeted at advanced undergraduate or graduate students, faculty members, and researchers from both industry and academia. … I highly recommend this book to someone who is starting to explore the field of graph mining or wants to delve deeper into this exciting field.” (Dimitrios Katsaros, ACM Computing Reviews, December, 2010)
