A Hybrid Cluster-Lift Method for the Analysis of Research Activities

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.

• Type: Conference
• Year: 2010
• Where: HAIS
• Authors: Boris Mirkin, Susana Nascimento, Trevor I. Fenner, Luís Moniz Pereira
• Keywords: ACM Computing Classification System, Artificial Intelligence, Fuzzy Spectral Clustering, HAIS 2010, Spectral Clustering