Ontology based text clustering using the dissimilarity measure

摘要

Performance of the text clustering can be improved by using ontologies. Before implementing the clustering process term mutual information matrix is calculated with the aid of the background knowledge build to textual data. Then the K-Modes algorithm is used to cluster the textual data with the dissimilarity measure. This result to obtain clusters with strong intra-similarities and efficiently cluster large textual data.