Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.
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. Our approach aims at retrieving relevant information and to minimize the irrelevant information through user friendly and efficient search algorithms. The traditional solution employs keyword based search without the semantic consideration. So this 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, WordNet 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.
Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi