Multiple Query Processing via Logic Function Factoring

Matteo Catena, N. Tonellotto
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引用次数: 4

Abstract

Some extensions to search systems require support for multiple query processing. This is the case with query variations, i.e., different query formulations of the same information need. The results of their processing can be fused together to improve effectiveness, but this requires to traverse more than once the query terms' posting lists, thus prolonging the multiple query processing time. In this work, we propose an approach to optimize the processing of query variations to reduce their overall response time. Similarly to the standard Boolean model, we firstly represent a group of query variations as a logic function where Boolean variables represent query terms. We then apply factoring to such function, in order to produce a more compact but logically equivalent representation. The factored form is used to process the query variations in a single pass over the inverted index. We experimentally show that our approach can improve by up to 1.95× the mean processing time of a multiple query with no statistically significant degradation in terms of NDCG@10.
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基于逻辑函数分解的多重查询处理
搜索系统的一些扩展需要支持多个查询处理。查询变量就是这种情况,即相同信息需求的不同查询公式。它们的处理结果可以融合在一起以提高效率,但这需要遍历多次查询条件的发布列表,从而延长了多次查询处理时间。在这项工作中,我们提出了一种方法来优化查询变化的处理,以减少它们的总体响应时间。与标准布尔模型类似,我们首先将一组查询变量表示为逻辑函数,其中布尔变量表示查询项。然后,我们对这样的函数应用分解,以产生一个更紧凑但逻辑上等效的表示。因子形式用于在倒排索引的单次传递中处理查询变化。我们通过实验表明,我们的方法可以将多个查询的平均处理时间提高1.95倍,而在NDCG@10方面没有统计学上显著的下降。
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