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Cluster-based query expansion using language modeling in the biomedical domain

机译:在生物医学领域使用语言建模进行基于集群的查询扩展

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Several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve low search precision and low search recall issues. Of these techniques, this paper proposed cluster-based query expansion using language modeling. Through our experiments in TREC genomic track ad-hoc retrieval task, we explore and demonstrate clusters that are created based on the whole collection or the initially returned document results of the original query can be utilized to perform query expansion and eventually improve the overall effectiveness and performance of information retrieval system in the biomedical domain.
机译:已经开发了多种技术,例如查询扩展,基于聚类的检索和降维,以解决低搜索精度和低搜索召回问题。在这些技术中,本文提出了使用语言建模的基于集群的查询扩展。通过我们在TREC基因组轨道临时检索任务中的实验,我们探索并演示了基于整个集合创建的聚类,或者原始查询的最初返回的文档结果可用于执行查询扩展,并最终提高整体效率和信息检索系统在生物医学领域的性能。

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