Optimizing Merging Results of Multiple Resource Retrievals by a Particle Swarm Algorithm
Xing Xie · 2012
To automatically merge the result from multiple independent research engines ( IREs ) is a key component of the metasearch engine development and it is problem in distributed information retrieval applications as well. After testing a variety of existing result merging algorithms for multiple IRE results, a discrete particle swarm algorithm ( DPSA) is proposed for further optimizing a group of merging results produced by other result merging algorithms. The experimental results show that the DPSA generally outperforms all the other result merging algorithms. It usually has better adaptability in application for not having to take into account the usefulness weights of IRE results and the overlap rate among different IRE results of a query. Compared to other result merging algorithms,the recognition precision of DPSA increases nearly 20% ,while the precision standard deviation for different queries decreases about 50% .