A Visual Clustering Platform for Cluster's Interpretation and Quality Evaluation.

Today, the generalization of data processing in all the industry branches leads to the construction of large databases, The exploitation of these data in various fields calls upon analysis and knowledge extraction techniques. Clustering is one of the most used techniques. Several clustering platforms were proposed in order to allow an effective and fast data grouping, These platforms integrate various approaches. However, they present several limits. In this paper, we propose a new platform, called EvaICluster, which a) integrates several clustering approaches b) allows the data processing which coming from various data sources c) interprets graphically the clustering results and d) evaluates the clustering quality and e) calculates the performances of implemented approaches. [ABSTRACT FROM AUTHOR]