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Visualizing Web Search Results on the Basis of Snippet Similarity

Priyanka Daimary, Rachana Das, Sangita Kumari, Sakthipriya N

Search engines are programs that search documents for specified keywords and return list of documents where the keywords were found. Textual snippet based search enable us to search documents in a better way. Search tasks would be easier if users were given an overview of document clusters in an organized manner so as to show how related they are content wise. In this paper, we introduce a novel multi-viewpoint based similarity measure and two related clustering methods. Using multiple viewpoints, more informative assessment of similarity could be achieved. We also propose a visualization technique to display the results of web queries.

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