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Efficient Approximation of Well-Designed SPARQL Queries

机译:高效近似于精心设计的SPARQL查询

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Query response time often influences user experience in the real world. However, the time of answering a SPARQL query with its all exact solutions in large scale RDF dataset possibly exceeds users' tolerable waiting time, especially when it contains the OPT operations since the OPT operation is the least conventional operator in SPARQL. So it becomes essential to make a trade-off between the query response time and the accuracy of their solutions. That is, partial answers can be provided for users to reduce the response query time within their tolerable waiting time. In this paper, based on the depth of the OPT operation occurring in a query, we propose an approach to obtain its all approximate queries with less depth of the OPT operation. Although queries are approximated in this method, it remains the "non-optional" query patterns from users, This paper mainly discusses those queries with well-designed patterns since the OPT operation in a well-designed pattern is really "optional". We remove "optional" triple patterns with less depth of the OPT operation and then obtain approximate queries with different depths of the OPT operation. Furthermore, we evaluate the approximate query efficiency and solutions precision with the degree of approximation. It shows that users can keep the balance between query efficiency and solutions precision by changing the degree of approximation.
机译:查询响应时间通常会影响现实世界中的用户体验。然而,在大规模RDF数据集中回答SPARQL查询的时间可能超过用户可容忍的等待时间,特别是当您包含OPT操作是SPARQL中最不传统的操作员时,尤其是当它包含OPT操作时。因此,在查询响应时间和解决方案的准确性之间进行权衡变得重要。也就是说,可以为用户提供部分答案,以减少其可容忍的等待时间内的响应查询时间。在本文中,基于查询中的OPT操作的深度,我们提出了一种方法来获得其所有近似查询,其较少的OPT操作深度。虽然在这种方法中近似查询,但它仍然是来自用户的“非可选”查询模式,而本文主要讨论具有精心设计的模式的查询,因为在设计精心设计的图案中的OPT操作真的“可选”。我们删除了“可选”三重模式,深度较少的OPT操作,然后获得具有不同深度的近似查询。此外,我们评估了具有近似程度的近似查询效率和解决方案精度。它表明,用户可以通过改变近似程度来保持查询效率和解决方案之间的平衡。

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