Name
Title | ||
|---|---|---|
Multiple data structure discovery through global optimisation, meta clustering and consensus methods |
Abstract | ||
|---|---|---|
When dealing with real data, clustering becomes a very complex problem, usually admitting many reasonable solutions. Moreover, even if completely different, such solutions can appear almost equivalent from the point of view of classical quality measures such as the distortion value. This implies that blind optimisation techniques alone are prone to discard qualitatively interesting solutions. In this work we propose a systematic approach to clustering, including the generation of a number of good solutions through global optimisation, the analysis of such solutions through meta clustering and the final construction of a small set of solutions through consensus clustering. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1504/IJKESDP.2009.028984 | IJKESDP |
Keywords | Field | DocType |
qualitatively interesting solution,final construction,distortion value,good solution,meta clustering,multiple data structure discovery,classical quality,consensus clustering,blind optimisation technique,global optimisation,consensus method,complex problem,data structure | Fuzzy clustering,Data mining,CURE data clustering algorithm,Clustering high-dimensional data,Correlation clustering,Consensus clustering,Constrained clustering,Artificial intelligence,Conceptual clustering,Cluster analysis,Machine learning,Mathematics | Journal |
Volume | Issue | Citations |
1 | 4 | 2 |
PageRank | References | Authors |
0.43 | 16 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ida Bifulco | 1 | 16 | 3.54 |
| Carmine Fedullo | 2 | 7 | 1.57 |
| Francesco Napolitano | 3 | 61 | 5.16 |
| Giancarlo Raiconi | 4 | 118 | 15.08 |
| Roberto Tagliaferri | 5 | 428 | 55.64 |