Hybrid Approach for Optimizing the Search Engine Result

Due to tremendous growth in growth of internet over recent years, huge amount of data collected over the web and search engine users facing problem in search a relevant information by writing few keywords, search engine returns a number of result page and then user have to spend long time to search a relevant information from number of result. In this paper, we propose a hybrid approach for optimizing the search engine results using document clustering, genetic algorithm and Query Recommendation to provide the user with the most relevant pages to the search query. This process starts with query recommendation, based on learning from query logs that predicts user information requirements in which an algorithm has been applied to recommend related queries to a query submitted by user and process of document clustering, genetic algorithm are applied to resultant pages from query recommendation to deliver most relevant result to user at minimum time. Keywords— Document Clustering; Genetic Algorithm; search engine; Query Recommendation; Hybrid model