Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps

Nohuddin Puteri Nor Ellyza, Frans Coenen, Rob Christley, Christian Setzkorn, Yogesh Patel, Shane Williams

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

This paper introduces a technique that uses frequent pattern mining and SOM techniques to identify, group and analyse trends in sequences of time stamped social networks so as to identify "interesting" trends. In this study, trends are defined in terms of a series of occurrence counts associated with frequent patterns that may be identified within social networks. Typically a large number of frequent patterns, and by extension a large number of trends, are discovered. Thus, to assist with the analysis of the discovered trends, the use of SOM techniques is advocated so that similar trends can be grouped together. To identify "interesting" trends a sequences of SOMs are generated which can be interpreted by considering how trends move from one SOM to the next. The further a trend moves from one SOM to the next, the more "interesting" the trend is deemed to be. The study is focused two types of network, Star networks and Complex star networks, exemplified by two real applications: the Cattle Tracing System in operation in Great Britain and a car insurance quotation application.

Original languageEnglish
Pages (from-to)104-113
Number of pages10
JournalKnowledge-Based Systems
Volume29
DOIs
Publication statusPublished - May 2012
Externally publishedYes

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Self organizing maps
Stars
Insurance
Railroad cars
Social networks
Pattern mining
Self-organizing map

Keywords

  • Clustering
  • Frequent pattern mining
  • Self organizing maps
  • Social networks
  • Trends

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Management Information Systems
  • Information Systems and Management

Cite this

Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps. / Puteri Nor Ellyza, Nohuddin; Coenen, Frans; Christley, Rob; Setzkorn, Christian; Patel, Yogesh; Williams, Shane.

In: Knowledge-Based Systems, Vol. 29, 05.2012, p. 104-113.

Research output: Contribution to journalArticle

Puteri Nor Ellyza, Nohuddin ; Coenen, Frans ; Christley, Rob ; Setzkorn, Christian ; Patel, Yogesh ; Williams, Shane. / Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps. In: Knowledge-Based Systems. 2012 ; Vol. 29. pp. 104-113.
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