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A robust validation framework for trend mining : a study in diabetic retinopathy

Somaraki, V. and McCluskey, T.L. (2012) A robust validation framework for trend mining : a study in diabetic retinopathy. In: Proceedings of The Queen’s Diamond Jubilee Computing and Engineering Annual Researchers’ Conference 2012: CEARC’12. University of Huddersfield, Huddersfield, pp. 63-68. ISBN 978-1-86218-106-9

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Abstract

Data mining is concerned with the identification of hidden patterns in data. Trand mining is a branch of data mining that focusses on the process to identify and analyze hidden trends in temporal data. A novel trend mining framework is described in this paper. The framework considers trends in terms of sequences of support values associate with frequent items sets and uses a trend mining algorithm that produces prototypes trends. To validate the framework in the analysis of the generated trends a mechanism is also proposed. The framework is evaluated using longitudinal Diabetic Retinopathy screening data.

Item Type: Book Chapter
Uncontrolled Keywords: Validation trend mining Longitudinal data Temporal databases
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge

School of Computing and Engineering > Pedagogical Research Group
Related URLs:
Depositing User: Sharon Beastall
Date Deposited: 01 May 2012 11:38
Last Modified: 01 May 2012 11:38
URI: http://eprints.hud.ac.uk/id/eprint/13451

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