Science and Development Network (SciDev.Net)
Web clustering engine greatly simplifies the effort of the user from browsing the large set of search results by reorganizing them into smaller clusters. Current web clustering engines result in additional clusters and misses out few relevant, leading to lack of predictability of clustering outputs. Web clustering engines produces inconsistent results as the content of the cluster do not always correspond to its label. In this paper, a new web clustering engine named SRCluster has been proposed to overcome these deficiencies, in specific for the polysemy unigram search keywords. SRCluster identifies the possible categories and its label for the given polysemy keyword based on Wikipedia.