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Effects Of Similarity Metrics On Document Clustering, Rushikesh Veni
Effects Of Similarity Metrics On Document Clustering, Rushikesh Veni
UNLV Theses, Dissertations, Professional Papers, and Capstones
Document clustering or unsupervised document classification is an automated process of grouping documents with similar content. A typical technique uses a similarity function to compare documents. In the literature, many similarity functions such as dot product or cosine measures are proposed for the comparison operator.
For the thesis, we evaluate the effects a similarity function may have on clustering. We start by representing a document and a query, both as a vector of high-dimensional space corresponding to the keywords followed by using an appropriate distance measure in k-means to compute similarity between the document vector and the query vector to …