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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 > Informatics Research Group School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces School of Computing and Engineering > Pedagogical Research Group |
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| Depositing User: | Sharon Beastall |
| Date Deposited: | 01 May 2012 12:38 |
| Last Modified: | 01 May 2012 12:38 |
| URI: | http://eprints.hud.ac.uk/id/eprint/13451 |
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