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Comparison Clustering using Cosine and Fuzzy set based Similarity Measures of Text Documents
May 01, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Manan Mohan Goyal, Neha Agrawal, Manoj Kumar Sarma, Nayan Jyoti Kalita
arXiv ID
1505.00168
Category
cs.IR: Information Retrieval
Citations
6
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Keeping in consideration the high demand for clustering, this paper focuses on understanding and implementing K-means clustering using two different similarity measures. We have tried to cluster the documents using two different measures rather than clustering it with Euclidean distance. Also a comparison is drawn based on accuracy of clustering between fuzzy and cosine similarity measure. The start time and end time parameters for formation of clusters are used in deciding optimum similarity measure.
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