Mirkin, Boris and Nascimento, S. and Pereira, L.M. (2008) Representing a computer science research organization on the ACM computing classification system. Supplementary Proceedings of the 16th International Conference on Conceptual Structures 354 , pp. 57-65. ISSN 1613-0073.
Abstract
We propose a method, Cluster-Lift, for parsimoniously mapping clusters of ontology classes of lower levels onto a subset of high level classes in such a way that the latter can be considered as a generalized description of the former. Specifically, we consider the problem of visualization of activities of a Computer Science Research organization on the ACM Computing Subjects Classification (ACMC), which is a three level taxonomy. It is possible to specify the set of ACMC subjects that are investigated by the organization’s teams and individual members and map them to the ACMC hierarchy. This visualization, however, usually appears overly detailed, confusing, and difficult to interpret. This is why we propose a two-stage Cluster-Lift procedure. On the first stage, the subjects are clustered according to their similarity defined in such a way that the greater the number of researchers working on a pair of subjects, the greater the similarity between the pair. On the second stage, each subject cluster is mapped onto ACMC and lifted within the taxonomy. The lifting involves a formalization of the concept of “head subject”, as well as its “gaps” and “offshoots” and is to be done in a parsimonious way by minimizing a weighted sum of the numbers of head subjects, gaps and offshoots. The Cluster-Lift results are easy to see and interpret. A real-world example of the working of our approach is provided.
Metadata
| Item Type: | Article |
|---|---|
| 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: | 26 Jul 2013 09:33 |
| Last Modified: | 09 Aug 2023 12:33 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/7839 |
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