Identification and visualisation of pattern migrations in big network data

Authors:
Puteri N. E. Nohuddin;Frans Coenen;Rob Christley;Wataru Sunayama
Affiliations:
Department of Computer Science, University of Liverpool, UK, Universiti Pertahanan Nasional Malaysia, Kuala Lumpur, Malaysia;Department of Computer Science, University of Liverpool, UK;School of Veterinary Science, University of Liverpool and National Centre for Zoonosis Research, Leahurst, Neston, UK;Graduate School of Information Sciences, Hiroshima City University, Japan
Venue:
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Year:
2012

Citing 3
Cited 0

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Abstract

In this paper, we described a technique for identifying and presenting frequent pattern migrations in temporal network data. The migrations are identified using the concept of a Migration Matrix and presented using a visualisation tool. The technique has been built into the Pattern Migration Identification and Visualisation (PMIV) framework which is designed to operate using trend clusters which have been extracted from "big" network data using a Self Organising Map technique.