Revisiting Condorcet Fusion

Liron Tyomkin, Oren Kurland
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Abstract

The fusion task is to aggregate ranked document lists retrieved for a query. The Condorcet voting criterion served as inspiration for a commonly used fusion method proposed by Montague and Aslam (2002). The method is stochastic as it is based on the QuickSort sorting algorithm. We empirically show that the performance of the method can substantially vary due to this stochastic aspect. We propose approaches that improve the performance robustness of this fusion method with respect to its stochastic nature. The resultant performance is on par with the state-of-the-art.
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回顾孔多塞融合
融合任务是聚合为查询检索的排序文档列表。Condorcet投票标准为Montague和Aslam(2002)提出的一种常用的融合方法提供了灵感。该方法是随机的,因为它是基于快速排序算法。我们的经验表明,由于这种随机方面,该方法的性能可能会发生很大的变化。我们提出了提高该融合方法的性能鲁棒性的方法。由此产生的性能与最先进的水平相当。
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