survey

Public Access

Graph Summarization Methods and Applications: A Survey

Authors:

Abhilash Dighe,

Danai KoutraAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 51, Issue 3

Article No.: 62, Pages 1 - 34

https://doi.org/10.1145/3186727

Published: 22 June 2018 Publication History

Abstract

While advances in computing resources have made processing enormous amounts of data possible, human ability to identify patterns in such data has not scaled accordingly. Efficient computational methods for condensing and simplifying data are thus becoming vital for extracting actionable insights. In particular, while data summarization techniques have been studied extensively, only recently has summarizing interconnected data, or graphs, become popular. This survey is a structured, comprehensive overview of the state-of-the-art methods for summarizing graph data. We first broach the motivation behind and the challenges of graph summarization. We then categorize summarization approaches by the type of graphs taken as input and further organize each category by core methodology. Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the field.

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 51, Issue 3

May 2019

796 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3212709

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL 32611

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Publication History

Published: 22 June 2018

Accepted: 01 February 2018

Revised: 01 January 2018

Received: 01 December 2016

Published in CSUR Volume 51, Issue 3

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