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- W138719796 abstract "Of late, people are using Internet to retrieve information from a vast web repository. As a query, a word or a group of words can imply multiple meanings in different contexts. Web search engine, however, cannot distinguish the context and hence retrieves huge information. It becomes a tedious job for users to browse all web pages until they reach to the target one. To overcome the problem, researchers proposed to present search result in cluster form where web pages of a search result are grouped based on their similarity measures. So, the user gets proper guidance to find out their target web pages with fewer trials. After analyzing the basic clustering approaches we propose a clustering algorithm combining k-Means and hierarchical clustering to obtain better cluster quality with affordable time delay. We compare the proposed method with the existing methods. The experimental result substantiates the efficacy of the proposed method.KeywordsWeb searchingInformation retrievalDocument clusteringClustering algorithm" @default.
- W138719796 created "2016-06-24" @default.
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- W138719796 date "2014-01-01" @default.
- W138719796 modified "2023-09-27" @default.
- W138719796 title "Clustering Web Search Results to Identify Information Domain" @default.
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- W138719796 doi "https://doi.org/10.1007/978-81-322-1817-3_30" @default.
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