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Jyoti Mor, Naresh Kumar, Dinesh Rai


The web is changing momentarily which makes it very difficult for the user to retrieve relevant results as per the given query. Clustering is a technique to organize search results in a way so that same search results are associated only with one cluster. For clustering of web pages, different parts of the webpage can be used. There are the lot of algorithms like K-means, Apriori, Expectation maximization, Ada etc. are used for clustering of documents. Clustering Algorithm such as K-means suffers from various problems such as less efficiency and clusters with large entropy. This paper overcomes the problems of K means and makes the use of bisecting K-means algorithm as the primary clustering algorithm having linear time.


Meta Search Engine; Search Engine; Webpage; Clustering and Ranking Meta Search Engine

Full Text:



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S.Poomagal and Dr. T. Hamsapriya, ”K-means for Search Results clustering using URL and Tag contents,” International Conference on Process Automation, Control and Computing, pp.1-7, ISSN: 978-1-61284-764-1, 2011.

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