The application of social network mining to cattle movement analysis: introducing the predictive trend mining framework

Nohuddin, P, Coenen, F ORCID: 0000-0003-1026-6649 and Christley, R ORCID: 0000-0001-9250-3032 (2016) The application of social network mining to cattle movement analysis: introducing the predictive trend mining framework. Social Network Analysis and Mining, 6 (1). 45:1-45:1.

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Abstract

This paper describes a predictive social network mining framework which is demonstrated using the Great Britain cattle movement datasets. The proposed framework, the predictive trend mining framework (PTMF), is used to analyse episodes of time-stamped social network data. The PTMF has two main components (1) a frequent pattern trend analysis component that efficiently identifies temporal frequent patterns and trends and also provides a mechanism for clustering and analysing these patterns and trends so as to detect dynamic changes within the cattle movement network, and (2) the predictive modelling component for forecasting the percolation of information or data across the network. The PTMF incorporates a number of novel elements including mechanisms to: (1) identify temporal frequent patterns and trends, (2) cluster large sets of trends, (3) analyse temporal clusters for pattern trend change detection, (4) visualise these changes using pattern migration network maps and (5) predict the paths whereby information moves across the network over time.

Item Type:	Article
Depositing User:	Symplectic Admin
Date Deposited:	01 Feb 2017 10:02
Last Modified:	23 Nov 2023 03:45
DOI:	10.1007/s13278-016-0353-x
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3005486