Community Search over Big Graphs

You must be logged in to access this title.

Sign up now

Already a member? Log in

Synopsis

Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention, from small, simple, and static graphs to big, evolving, attributed, and location-based graphs.
In this book, we first review the basic concepts of networks, communities, and various kinds of dense subgraph models. We then survey the state of the art in community search techniques on various kinds of networks across different application areas. Specifically, we discuss cohesive community search, attributed community search, social circle discovery, and geo-social group search. We highlight the challenges posed by different community search problems. We present their motivations, principles, methodologies, algorithms, and applications, and provide a comprehensive comparison of the existing techniques. This book finally concludes by listing publicly available real-world datasets and useful tools for facilitating further research, and by offering further readings and future directions of research in this important and growing area.

Book details

Series:
Synthesis Lectures on Data Management
Author:
Xin Huang, Laks V.S. Lakshmanan, Jianliang Xu
ISBN:
9783031018749
Related ISBNs:
9783031001017
Publisher:
Springer International Publishing
Pages:
N/A
Reading age:
Not specified
Includes images:
No
Date of addition:
2022-06-01
Usage restrictions:
Copyright
Copyright date:
2019
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Nonfiction