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Title: A Novel Vertex Affinity for Community Detection

Abstract

We propose a novel vertex affinity measure in this paper. The new vertex affinity quantifies the proximity between two vertices in terms of their clustering strength and is ideal for such graph analytics applications as community detection. We also developed a framework that combines simple graph searches and resistance circuit formulas to compute the vertex affinity efficiently. We study the properties of the new affinity measure empirically in comparison to those of other popular vertex proximity metrics. Our results show that the existing metrics are ill-suited for community detection due to their lack of fundamental properties that are essential for correctly capturing inter- and intra-cluster vertex proximity.

Authors:
 [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1226940
Report Number(s):
LLNL-TR-677840
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Yoo, Andy, Sanders, Geoffrey, Henson, Van, and Vassilevski, Panayot. A Novel Vertex Affinity for Community Detection. United States: N. p., 2015. Web. doi:10.2172/1226940.
Yoo, Andy, Sanders, Geoffrey, Henson, Van, & Vassilevski, Panayot. A Novel Vertex Affinity for Community Detection. United States. https://doi.org/10.2172/1226940
Yoo, Andy, Sanders, Geoffrey, Henson, Van, and Vassilevski, Panayot. 2015. "A Novel Vertex Affinity for Community Detection". United States. https://doi.org/10.2172/1226940. https://www.osti.gov/servlets/purl/1226940.
@article{osti_1226940,
title = {A Novel Vertex Affinity for Community Detection},
author = {Yoo, Andy and Sanders, Geoffrey and Henson, Van and Vassilevski, Panayot},
abstractNote = {We propose a novel vertex affinity measure in this paper. The new vertex affinity quantifies the proximity between two vertices in terms of their clustering strength and is ideal for such graph analytics applications as community detection. We also developed a framework that combines simple graph searches and resistance circuit formulas to compute the vertex affinity efficiently. We study the properties of the new affinity measure empirically in comparison to those of other popular vertex proximity metrics. Our results show that the existing metrics are ill-suited for community detection due to their lack of fundamental properties that are essential for correctly capturing inter- and intra-cluster vertex proximity.},
doi = {10.2172/1226940},
url = {https://www.osti.gov/biblio/1226940}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Oct 05 00:00:00 EDT 2015},
month = {Mon Oct 05 00:00:00 EDT 2015}
}