Name
Abstract | ||
|---|---|---|
This paper introduces a new topological clustering formalism, dedicated to categorical data arising in the form of a binary matrix or a sum of binary matrices. The proposed approach is based on the principle of the Kohonen's model (conservation of topological order) and uses the Relational Analysis formalism by optimizing a cost function defined as a Condorcet criterion. We propose an hybrid algorithm, which deals linearly with large datasets, provides a natural clusters identification and allows a visualization of the clustering result on a two dimensional grid while preserving the a priori topological order of the data. The proposed approach called RTC was validated on several datasets and the experimental results showed very promising performances. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IJCNN.2010.5596926 | IJCNN |
Keywords | DocType | ISSN |
relational analysis formalism,pattern clustering,condorcet criterion,topological clustering formalism,kohonen model,data analysis,relational topological clustering,hybrid algorithm,self-organising feature maps,visualization,cost function,categorical data | Conference | 1098-7576 |
ISBN | Citations | PageRank |
978-1-4244-6916-1 | 1 | 0.38 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lazhar Labiod | 1 | 34 | 13.50 |
| Nistor Grozavu | 2 | 67 | 16.76 |
| Younès Bennani | 3 | 269 | 53.18 |