Title :
Ontology based text clustering using the dissimilarity measure
Author_Institution :
M.E Dept. of CSE, Anna Univ., Tiruchirappalli, India
Abstract :
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.
Keywords :
ontologies (artificial intelligence); pattern clustering; text analysis; dissimilarity measure; k-modes algorithm; ontology; term mutual information matrix; text clustering; Algorithm design and analysis; Clustering algorithms; Euclidean distance; Mutual information; Ontologies; Partitioning algorithms; Symmetric matrices; K-Modes; categorical data; clustering; ontology;
Conference_Titel :
Communication and Computational Intelligence (INCOCCI), 2010 International Conference on
Conference_Location :
Erode
Electronic_ISBN :
978-81-8371-369-6
