Provided by: International Journal of Computer Theory and Engineering (IJCTE)
Topic: Big Data
Date Added: Feb 2014
The possibility to face pattern recognition problems directly on structured domains (e.g., multimedia data, strings and graphs) is fundamental to the effective solution of many interesting applications. In this paper, the authors deal with a clustering problem defined in the string domain, focusing on the problem of cluster representation in data domains where only a dissimilarity measure can be fixed. To this aim, they adopt the MinSOD (Minimum Sum Of Distances) cluster representation technique, which defines the representative as the element of the cluster minimizing the sum of dissimilarities from all the other elements in the considered set.