DocumentCode
541786
Title
Ontology based text clustering using the dissimilarity measure
Author
Binisha, R.
Author_Institution
M.E Dept. of CSE, Anna Univ., Tiruchirappalli, India
fYear
2010
fDate
27-29 Dec. 2010
Firstpage
476
Lastpage
480
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication and Computational Intelligence (INCOCCI), 2010 International Conference on
Conference_Location
Erode
Electronic_ISBN
978-81-8371-369-6
Type
conf
Filename
5738777
Link To Document