结合句子级检索的信息检索模型

Jiali Zuo, Mingwen Wang, Jianyi Wan, Wenbing Luo
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引用次数: 2

摘要

为了获得更好的性能,一些研究人员提出了在语言模型中利用查询词的位置和接近度信息的相关工作。但这些模型需要大量的训练数据,且计算复杂度较高。本文提出了一种结合句子级检索和以句子为单位计算句子与查询的关联度的信息检索模型。实验结果表明,该模型的性能优于基准模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information Retrieval Model Combining Sentence Level Retrieval
To get better performance, Some researchers have proposed relative work to exploit the position and proximity information of query terms in language model. However these models need large quantity of training data and its computation complexity is comparatively high. This paper presents an information retrieval model combining sentence level retrieval and use sentence as a unit to compute the relevant degree of the sentence to query. Experiment results show our model can get better performance than baseline models.
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