A Comparative Analysis of Particle Swarm Optimization and K-means Algorithm For Text Clustering Using Nepali Wordnet

@inproceedings{Sarkar2014ACA,
  title={A Comparative Analysis of Particle Swarm Optimization and K-means Algorithm For Text Clustering Using Nepali Wordnet},
  author={Sunita Sarkar and Arindam Roy and Bipul Shyam Purkayastha},
  year={2014}
}
The volume of digitized text documents on the web have been increasing rapidly. As there is huge collection of data on the web there is a need for grouping(clustering) the documents into clusters for speedy information retrieval. Clustering of documents is collection of documents into groups such that the documents within each group are similar to each other and not to documents of other groups. Quality of clustering result depends greatly on the representation of text and the clustering… CONTINUE READING

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