Description

Abstract

Conventional document agglomeration techniques area unit mainly supported the existence

of keywords and also the variety of occurrences of it. Most of the term frequency primarily

based agglomeration techniques contemplate the documents as bag-of-words and ignore the

necessary relationships between the words within the document. It uses Medical Subject

Headings MeSH ontology for conception extraction and conception weight calculation based

on the identity and synonymity relationships. K-means algorithm is employed for

agglomeration the documents supported the semantic similarity and also the results area unit

analyzed.