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Explicit Search Result Diversification through Sub-queries

机译:通过子查询的明确搜索结果多样化

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Queries submitted to a retrieval system are often ambiguous. In such a situation, a sensible strategy is to diversify the ranking of results to be retrieved, in the hope that users will find at least one of these results to be relevant to their information need. In this paper, we introduce xQuAD, a novel framework for search result diversification that builds such a diversified ranking by explicitly accounting for the relationship between documents retrieved for the original query and the possible aspects underlying this query, in the form of sub-queries. We evaluate the effectiveness of xQuAD using a standard TREC collection. The results show that our framework markedly outperforms state-of-the-art diversification approaches under a simulated best-case scenario. Moreover, we show that its effectiveness can be further improved by estimating the relative importance of each identified sub-query. Finally, we show that our framework can still outperform the simulated best-case scenario of the state-of the-art diversification approaches using sub-queries automatically derived from the baseline document ranking itself.
机译:提交给检索系统的查询通常是模棱两可的。在这种情况下,明智的策略是使要检索的结果的排名多样化,以希望用户找到这些结果中的至少一个与其信息需求相关。在本文中,我们介绍了xQuAD,这是一种用于搜索结果多样化的新颖框架,该框架通过以子查询的形式明确说明原始查询所检索的文档与该查询所基于的可能方面之间的关系,从而建立了这样的多元化排名。我们使用标准TREC集合评估xQuAD的有效性。结果表明,在模拟的最佳情况下,我们的框架明显优于最新的多元化方法。而且,我们表明,通过估计每个已标识子查询的相对重要性,可以进一步提高其有效性。最后,我们证明了我们的框架仍然可以使用从基线文档排名本身自动得出的子查询,胜过最新的多样化方法的模拟最佳情况。

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