Interactive Interpretation of Hierarchical Clustering

Article type: Research Article

Authors: Boudaillier, Eric | Hebrail, Georges^{; *}

Affiliations: Electricité de France – Research Center, 1 Av. du Général de Gaulle, 92141 Clamart, Cedex, France

Correspondence: [*] Corresponding author. E-mail: Georges.Hebrail@der.edfgdf.fr.

Abstract: Automatic clustering methods are part of data mining methods. They aim at building clusters of items so that similar items fall into the same cluster while unsimilar items fall into separate clusters. A particular class of clustering methods are hierarchical ones where recursive clusters are formed to grow a binary tree representing an approximation of similarities between items. We propose a new interactive interface to help the user to interpret the result of such a clustering process, according to the item characteristics. The prototype has been applied successfully to a special case of items providing nice graphical representations (electric load curves) but can also be used with other types of curves or with more standard items.

Keywords: Hierarchical clustering, Computer-human interface, Interpretation of clustering, Curve clustering

DOI: 10.3233/IDA-1998-2306

Journal: Intelligent Data Analysis, vol. 2, no. 3, pp. 229-244, 1998