Study of Optimizing the Merging Results of Multiple Resource Retrieval Systems by a Particle Swarm Algorithm
XinSheng Xie, Guoliang Zhang · 2011
The result merging for multiple independent resource retrieval systems (IRRSs), which is a key component in developing the metasearch engine, is a difficult problem that still not effectively solved in distributed information retrieving areas. After investigating a variety of existing result merging algorithms for combination multiple IRRS results, we proposed a Discrete Particle Swarm Algorithm (DPSA) that is able to further coalesce and optimize a group of merging results produced by other existing result merging algorithms. The experimental results show that: the DPSA, not only can overall outperform all the other result merging algorithms it employed, but also has better adaptability in application for unnecessarily taking into account the usefulness weights of IRRS results and the overlap rate among different IRRS results with respect to concrete query.