Odd and even point crossover based Tabu ga for data fusion in Information retrieval

Abstract

The retrieval schemes arrange process and list the documents in the newlinecorpus against the user query The schemes differ from each other in any one newlineof the above mentioned mechanisms Hence the literature has been flooded newlinewith various retrieval models and schemes The merits of the various schemes newlinecan be merged together to enhance the overall performance of the retrieval newlinesystems The merging process again depends on the proper selection of newlineindividual schemes participating in the merging The optimization searching newlinetools are used for selection This work indents to use Genetic Algorithm GA newlineas the tool and we plan to test the impact of odd and even point crossover newlineOdd and Even point cross over is mainly used as the exploration tool and the newlineimpact is tested over data fusion in information retrieval newlineThe fusion function retrieval schemes and their weights leads to a newlinehuge combination Finding an optimal solution from this huge combination is newlineentirely based on the exploration We used odd and even point crossover as newlinean exploration tool This exploration tool suffers a setback of convergence newlineThe convergence rate can be improved by merging Tabu search a best local newlineSearch with the genetic algorithm newline newline