A Survey on K-means Clustering and Web-Text Mining
Journal: International Journal of Science and Research (IJSR) (Vol.5, No. 4)Publication Date: 2016-04-05
Authors : Aayushi Bindal; Analp Pathak;
Page : 1049-1052
Keywords : Text Mining; Web Mining; K-means Clustering Algorithm; Weighted Page Rank;
Abstract
we are presenting a survey on the k-means clustering and web-text mining. Text mining refers to the extracting useful concepts from the text and Web mining refers to finding the useful and previously unknown information from the web. As we required more time to search the research papers. It consumes more time to read a single paper. So it is necessary to move forward new search engine based on fastest reading model. The main problem is that Ranking of research papers does not allotted. K-Means clustering refers in which the given data set is divided into K number of cluster. So in order to reduce the execution time we are using the weighted page rank with k means clustering. We will present the research related to assign the ranks of research papers on the basis of popularity of papers.
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