On Uncertain Graphs

On Uncertain Graphs

EnglishPaperback / softbackPrint on demand
Khan, Arijit
Springer, Berlin
EAN: 9783031007323
Print on demand
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Detailed information

Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
EAN 9783031007323
ISBN 3031007328
Binding Paperback / softback
Publisher Springer, Berlin
Publication date July 23, 2018
Pages 80
Language English
Dimensions 235 x 191
Country Switzerland
Readership Professional & Scholarly
Authors Chen, Lei; Khan, Arijit; Ye, Yuan
Illustrations XIII, 80 p.
Series Synthesis Lectures on Data Management
Manufacturer information
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