Demonstrating Interactive SPARQL Formulation through Positive and Negative Examples and Feedback

Akritas Akritidis, Yannis Tzitzikas
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Abstract

The formulation of structured queries in Knowledge Graphs is a challenging task since it presupposes familiarity with the syntax of the query language and the contents of the knowledge graph. To alleviate this problem, for enabling plain users to formulate SPARQL queries, and advanced users to formulate queries with less effort, in this paper we introduce a novel method for “SPARQL by Example". According to this method the user points to positive/negative entities, the system computes one query that describes these entities, and then the user refines the query interactively by providing positive/negative feedback on entities and suggested constraints. We shall demonstrate SPARQL-QBE , a tool that implements this approach, and we will briefly refer to the results of a task-based evaluation with users that provided positive evidence about the usability of the approach.
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通过正负例子和反馈演示交互式SPARQL公式
知识图中结构化查询的表述是一项具有挑战性的任务,因为它以熟悉查询语言的语法和知识图的内容为前提。为了缓解这一问题,使普通用户能够更轻松地制定SPARQL查询,而高级用户也能够更轻松地制定查询,本文介绍了一种“SPARQL by Example”的新方法。根据该方法,用户指向正/负实体,系统计算一个描述这些实体的查询,然后用户通过对实体和建议约束提供正/负反馈来交互式地改进查询。我们将演示SPARQL-QBE,这是一个实现此方法的工具,我们将简要地引用基于任务的用户评估的结果,该结果提供了关于该方法可用性的积极证据。
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