Result Merging Using Modified Bayesian Method for Meta Search Engine

Meta Search Engine search user query in multiple search engine and produce a merged result. Many merging result algorithms are proposed, but actual success of a Meta Search Engine depends on the degree of accuracy precision and user satisfaction. Accuracy precision and satisfaction directly depends on the merging approach and quality of search result presented. This paper proposed a novel result merging approach using modified Bayesian method to improvise the merging technique. The proposed approach based on the local rank and position rank of the retrieved results. The algorithm provides the right value information and decision-making process to provide the necessary data and solve information retrieval, ambiguity and processing uncertainty. The proposed approach experimentally evaluated to measure the improvisation of merging mechanisms for Meta Search Engine in comparing the popular search engines results.