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Evaluation of Score Standardization Methods for Web Search in Support of Results Diversification

机译:支持结果多样化的Web搜索评分标准化方法的评估

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摘要

Score standardization is a necessary step for many different types of Web search tasks in which results from multiple components need to be combined or re-ranked. Some recent studies suggest that score standardization may have impact on the performance of some typical explicit search result diversification methods such as XQuAD. In this paper, we evaluate the performance of six score standardization methods. Experiments with TREC data are carried out with two typical explicit result diversification methods XQuAD and PM2. We find that the reciprocal standardization method performs better than other score standardization methods in all the cases. Furthermore, we improve the reciprocal standardization method by scaling those scores up so as to better satisfy the requirement of probability scores and obtain better results with XQuAD. We confirm that score standardization has significant impact on the performance of explicit search result diversification methods and such a fact can be used to obtain more profitable score standardization methods and result diversification methods.
机译:分数标准化是许多不同类型的Web搜索任务的必要步骤,在这些任务中,来自多个组件的结果需要合并或重新排序。最近的一些研究表明,分数标准化可能会对某些典型的显式搜索结果多样化方法(例如XQuAD)的性能产生影响。在本文中,我们评估了六种评分标准化方法的性能。使用两种典型的显式结果多样化方法XQuAD和PM2对TREC数据进行了实验。我们发现,在所有情况下,对等标准化方法的性能均优于其他分数标准化方法。此外,我们通过按比例放大这些分数来改进对等标准化方法,以便更好地满足概率分数的要求,并使用XQuAD获得更好的结果。我们确认分数标准化对显式搜索结果多样化方法的性能具有重大影响,并且这一事实可用于获得更多可盈利的分数标准化方法和结果多样化方法。

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