Efficient Clustering Multiple Web Search Engine Results and Ranking
|R. Rubini1 and Dr. R. Manicka Chezian2
|Related article at Pubmed, Scholar Google|
World Wide Web is considered the most valuable place for Information Retrieval and Knowledge Discovery. Web search engines with effective and efficient techniques for Web service retrieval and selection becomes an important issue. Existing web search result based on keyword matching in single search engine only. This paper details a modular, self-contained web search results clustering system that enhances search results by (i) performing clustering on lists of web results returned by queries to search engines, and (ii) ranking the results and labeling the resulting clusters by using a calculated relevance value as a degree of membership to clusters. An efficient page ranking method is also proposed that orders the results according to both the relevancy and the importance of documents. Web search result clustering has been emerged as a method which overcomes these drawbacks of conventional information retrieval (IR) systems. This paper gives a sufficient overview and categorizes various techniques that have been used in clustering of web search results.