A Review on Document Clustering Using Concept Weight
Sapna Gupta, Vikrant Chole · 2014
Traditional document clustering techniques are mostly based on the number of occurrences and the existence of keywords. The term frequency based clustering techniques takes the documents as bag-of words while ignoring the relationship between the words. Similarly Phrase based clustering technique only captures the order in which the words appear in a sentence instead of determining the semantics behind the words. Considering the drawbacks of such system this paper proposes a concept based clustering technique. The ideology behind this concept is uses Medical Subjec t Headings MeSH ontology for extracting the concept and the concept weight calculation is done by its identity and relationship with its synonym. The method used for clustering documents on Semantic is called K-medoid algorithm through which the results are analyzed.