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Generating Query Facets Using Knowledge Bases

机译:使用知识库生成查询构面

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A query facet is a significant list of information nuggets that explains an underlying aspect of a query. Existing algorithms mine facets of a query by extracting frequent lists contained in top search results. The coverage of facets and facet items mined by these kind of methods might be limited, because only a small number of search results are used. In order to solve this problem, we propose mining query facets by using knowledge bases which contain high-quality structured data. Specifically, we first generate facets based on the properties of the entities which are contained in Freebase and correspond to the query. Second, we mine initial query facets from search results, then expanding them by finding similar entities from Freebase. Experimental results show that our proposed method can significantly improve the coverage of facet items over the state-of-the-art algorithms.
机译:查询构面是重要的信息块列表,用于解释查询的基础方面。现有算法通过提取包含在顶部搜索结果中的频繁列表来挖掘查询的各个方面。由于仅使用少量搜索结果,因此通过这些方法挖掘的构面和构面项的覆盖范围可能会受到限制。为了解决这个问题,我们建议通过使用包含高质量结构化数据的知识库来挖掘查询方面。具体来说,我们首先根据Freebase中包含并与查询相对应的实体的属性生成构面。其次,我们从搜索结果中挖掘初始查询构面,然后通过从Freebase查找相似实体来扩展它们。实验结果表明,相对于最新算法,我们提出的方法可以显着提高构面项的覆盖率。

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