Campus Units

Computer Science, Electrical and Computer Engineering

Document Type

Conference Proceeding

Conference

The 2019 World Wide Web Conference

Publication Version

Published Version

Publication Date

5-2019

Journal or Book Title

Companion Proceedings of the 2019 World Wide Web Conference (WWW '19 Companion)

First Page

1317

Last Page

1318

DOI

10.1145/3308560.3320092

Conference Title

The 2019 World Wide Web Conference

Conference Date

May 13–17, 2019

City

San Francisco, CA

Abstract

Subgraph counting is a fundamental problem in graph analysis that finds use in a wide array of applications. The basic problem is to count or approximate the occurrences of a small subgraph (the pattern) in a large graph (the dataset). Subgraph counting is a computationally challenging problem, and the last few years have seen a rich literature develop around scalable solutions for it. However, these results have thus far appeared as a disconnected set of ideas that are applied separately by different research groups. We observe that there are a few common algorithmic building blocks that most subgraph counting results build on. In this tutorial, we attempt to summarize current methods through distilling these basic algorithmic building blocks. The tutorial will also cover methods for subgraph analysis on “big data” computational models such as the streaming model and models of parallel and distributed computation.

Comments

This proceeding is published as Seshadhri, Comandur, and Srikanta Tirthapura. "Scalable Subgraph Counting: The Methods Behind The Madness." In Companion Proceedings of The 2019 World Wide Web Conference (WWW ’19 Companion), May 13– 17, 2019, San Francisco, CA, USA. New York, NY: ACM. (2019): 1317-1318. DOI: 10.1145/3308560.3320092. Posted with permission.

Copyright Owner

IW3C2 (International World Wide Web Conference Committee)

Language

en

File Format

application/pdf

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Article Location

 
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