Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Pereira, L.M. (2010) A hybrid cluster-lift method for the analysis of research activities. In: Romay, M. and GranaSebastian, M. and Garcia, T. (eds.) Hybrid Artificial Intelligence Systems. Lecture Notes in Artificial Intelligence 1 6076. Berlin, Germany: Springer Verlag, pp. 152-161. ISBN 9783642137693.
Abstract
A hybrid of two novel methods - additive fuzzy spectral clustering and lifting method over a taxonomy - is applied to analyse the research activities of a department. To be specific, we concentrate on the Computer Sciences area represented by the ACM Computing Classification System (ACM-CCS), but the approach is applicable also to other taxonomies. Clusters of the taxonomy subjects are extracted using an original additive spectral clustering method involving a number of model-based stopping conditions. The clusters are parsimoniously lifted then to higher ranks of the taxonomy by minimizing the count of “head subjects” along with their “gaps” and “offshoots”. An example is given illustrating the method applied to real-world data.
Metadata
| Item Type: | Book Section |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Structural Molecular Biology, Institute of (ISMB) |
| Depositing User: | Sarah Hall |
| Date Deposited: | 16 May 2013 15:56 |
| Last Modified: | 09 Aug 2023 12:33 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/6812 |
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