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Study of Optimizing the Merging Results of Multiple Resource Retrieval Systems by a Particle Swarm Algorithm

机译:粒子群算法优化多资源检索系统合并结果的研究

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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.
机译:作为元搜索引擎开发的关键组成部分的多个独立资源检索系统(IRRS)的结果合并是一个难题,但在分布式信息检索领域仍无法有效解决。在研究了用于组合多个IRRS结果的各种现有结果合并算法之后,我们提出了一种离散粒子群算法(DPSA),该算法能够进一步合并和优化由其他现有结果合并算法产生的一组合并结果。实验结果表明:DPSA不仅在总体上优于其使用的所有其他结果合并算法,而且在不必要地考虑IRRS结果的有用权重和不同IRRS结果之间的重叠率的情况下,在应用中具有更好的适应性。尊重具体的查询。

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