Wordnet Based Document Clustering

Madhavi Katamaneni, Ashok Cheerala

Abstract: Document clustering is considered as an important tool in the fast developing information explosion era. It is the process of grouping text documents into category groups and has found applications in various domains like information retrieval; web information systems. Ontology based computing is emerging as a natural evolution of existing technologies to design with the information onslaught. In current dissertation work; background knowledge derived from WordNet as ontology is applied during preprocessing of documents for document clustering. Document vectors constructed from WordNet synsets is used as input for clustering. Comparative analysis is done between clustering using k-means and clustering using bi-secting k-means. A document Categorization tool is developed which summarizes the hierarchy of concepts obtained from WordNet during clustering phase. GUI tool contains the association between WordNet concepts and documents belonging to the concept.

Keywords: Document clustering, Ontology, BOW, POS Tagging, Stemming, Labeling