Campus Units

Electrical and Computer Engineering, Computer Science

Document Type

Conference Proceeding

Conference

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

Publication Version

Accepted Manuscript

Link to Published Version

https://doi.org/10.1109/IPDPSW.2018.00182

Publication Date

2018

Journal or Book Title

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

First Page

1175

Last Page

1183

DOI

10.1109/IPDPSW.2018.00182

Conference Title

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

Conference Date

May 21-25, 2018

City

Vancouver, BC, Canada

Abstract

We present V2V, a method for embedding each vertex in a graph as a vector in a fixed dimensional space. Inspired by methods for word embedding such as word2vec, a vertex embedding is computed through enumerating random walks in the graph, and using the resulting vertex sequences to provide the context for each vertex. This embedding allows one to use well-developed techniques from machine learning to solve graph problems such as community detection, graph visualization, and vertex label prediction. We evaluate embeddings produced by V2V through comparing results obtained using V2V with results obtained through a direct application of a graph algorithm, for community detection. Our results show that V2V provides interesting trade-offs among computation time and accuracy.

Comments

This is a manuscript of a proceeding published as Nguyen, Trong Duc, and Srikanta Tirthapura. "V2V: Vector Embedding of a Graph and Applications." In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), (2018): 1175-1183. DOI: 10.1109/IPDPSW.2018.00182. Posted with permission.

Rights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

Published Version

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