Capturing missing edges in social networks using vertex similarity

Hung Hsuan Chen, Liang Gou, Xiaolong Zhang, Clyde Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We introduce the graph vertex similarity measure, Relation Strength Similarity (RSS), that utilizes a network's topology to discover and capture similar vertices. The RSS has the advantage that it is asymmetric; can be used in a weighted network; and has an adjustable "discovery range" parameter that enables exploration of friend of friend connections in a social network. To evaluate RSS we perform experiments on a coauthorship network from the CiteSeerX database. Our method significantly outperforms other vertex similarity measures in terms of the ability to predict future coauthoring behavior among authors in the CiteSeerX database for the near future 0 to 4 years out and reasonably so for 4 to 6 years out.

Original languageEnglish (US)
Title of host publicationKCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference
Pages195-196
Number of pages2
DOIs
StatePublished - 2011
Event6th International Conference on Knowledge Capture, KCAP 2011 - Banff, AB, Canada
Duration: Jun 26 2011Jun 29 2011

Publication series

NameKCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference

Other

Other6th International Conference on Knowledge Capture, KCAP 2011
CountryCanada
CityBanff, AB
Period6/26/116/29/11

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

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