Sciweavers

Share
ADMA
2010
Springer

Frequent Pattern Trend Analysis in Social Networks

10 years 27 days ago
Frequent Pattern Trend Analysis in Social Networks
Abstract. This paper describes an approach to identifying and comparing frequent pattern trends in social networks. A frequent pattern trend is defined as a sequence of time-stamped occurrence (support) values for specific frequent patterns that exist in the data. The trends are generated according to epochs. Therefore, trend changes across a sequence epochs can be identified. In many cases, a great many trends are identified and difficult to interpret the result. With a combination of constraints, placed on the frequent patterns, and clustering and cluster analysis techniques, it is argued that analysis of the result is enhanced. Clustering technique uses a Self Organising Map approach to produce a sequence of maps, one per epoch. These maps can then be compared and the movement of trends identified. This Frequent Pattern Trend Mining framework has been evaluated using two non-standard types of social networks, the cattle movement network and the insurance quote network.
Puteri N. E. Nohuddin, Rob Christley, Frans Coenen
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ADMA
Authors Puteri N. E. Nohuddin, Rob Christley, Frans Coenen, Yogesh Patel, Christian Setzkorn, Shane Williams
Comments (0)
books