Mining Web Graphs for Large Scale Meta Search Engine Results (International Journal of Engineering and Computer Science, 2017)
Web is huge, To get efficient result s from the search engine is difficult task. Meta search engine (MSE) is search tool that sends user requests to several search engines or databases, aggregates the results, Merges or re-ranks them into a single list and displays them to users with the help of web graphs .MSE enable users to enter search query once and access several search engines simultaneously. This technique saves lot of time to the user from having to use multiple search engines separately by initiating the search at a single point. Today’s Most of MSEs Employ only a small number of general purpose search engines. Building a large scale MSE using numerous specialized search engines is another area that deserves more attention. Arising challenges from building very large scale MSE includes automatic generation and Maintenance of high quality search engine representatives needed for efficient and effective search results, and highly automated Techniques to be added into MSE. In this paper, we are implementing our study on how to merge the search results returned from the multiple component search engines into a single ranked list through web graphs. Web graphs are essential for producing effective and efficient results.