Title

Mining Parameters That Characterize The Communities In Web-Like Networks

Keywords

Cyber communities; Graph mining; Random graphs; Statistical data mining

Abstract

Community mining in large, complex, real-life networks such as the World Wide Web has emerged as a key data mining problem with important applications. In recent years, several graph theoretic definitions of community, generally motivated by empirical observations and intuitive arguments, have been put forward. However, a formal evaluation of the appropriateness of such definitions has been lacking. We present a new framework developed to address this issue, and then discuss a particular implementation of this framework. Finally, we present a set of experiments aimed at evaluating the effectiveness of two specific graph theoretic structures-alliance and near-clique - in capturing the essential properties of communities. © 2006 IEEE.

Publication Date

11-22-2006

Publication Title

2006 IEEE International Conference on Granular Computing

Number of Pages

188-193

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

33751074433 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33751074433

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