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doi: 10.5281/zenodo.30110
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Clustering is the power full technique for segment relevant data into different levels. This study has proposed K-means clustering method for cluster web search results for search engines. For represent documents we used vector space model and use cosine similarity method for measure similarity between user query and the search results. As an improvement of K-means clustering we used distortion curve method for identify optimal initial number of clusters.
K-means clustering, Web Search, Search Engine, Vector space model, Distortion curve
K-means clustering, Web Search, Search Engine, Vector space model, Distortion curve
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