ONTOLOGY ORIENTED CONCEPT BASED CLUSTERING

Anbarasi.M.S, Iswarya.V, Sindhuja.M, Yogabindiya.S

Abstract: Worldwide health centre scientists, physicians and other patients are accessing, analyzing, integrating and storing massive amounts of digital medical data in different database. The potential for retrieval of information is vast and daunting. The objective of our approach is to differentiate relevant information from irrelevant through user friendly and efficient search algorithms. The traditional solution employs keyword based search without the semantic consideration. So the keyword retrieval may return inaccurate and incomplete results. In order to overcome the problem of information retrieval from this huge amount of database, there is a need for concept based clustering method in ontology. In the proposed method, WorldNet is integrated in order to match the synonyms for the identified keywords so as to obtain the accurate information and it presents the concept based clustering developed using k-means algorithm in accordance with the principles of ontology so that the importance of words of a cluster can be identified.

Keywords: Ontology, Concept based clustering, K-means algorithm and information retrieval

DOI: https://doi.org/10.15623/ijret.2014.0302106