论文标题
旨在从简单和部分出处的示例中推断查询
Towards Inferring Queries from Simple and Partial Provenance Examples
论文作者
论文摘要
典型查询的字段旨在通过找到绑定示例的基本逻辑来从非专家用户给出的输出示例中推断查询。但是，对于一小部分示例，很难正确地推断出这种逻辑。为了弥合这一差距，先前的工作建议将解释附加到每个输出示例，以出处为模型，从而使用户可以解释其选择示例背后的原因。在本文中，我们探讨了从一些输出示例和直观解释中推断查询的问题。我们提出了一个两步框架：（1）将解释转换为（部分）出处，（2）推断出使用采用基于图的方法的新算法生成输出示例的查询。该框架适用于非专家，因为它不需要全部规范出处或对其结构的理解。我们显示了我们方法的最初实验结果。
The field of query-by-example aims at inferring queries from output examples given by non-expert users, by finding the underlying logic that binds the examples. However, for a very small set of examples, it is difficult to correctly infer such logic. To bridge this gap, previous work suggested attaching explanations to each output example, modeled as provenance, allowing users to explain the reason behind their choice of example. In this paper, we explore the problem of inferring queries from a few output examples and intuitive explanations. We propose a two step framework: (1) convert the explanations into (partial) provenance and (2) infer a query that generates the output examples using a novel algorithm that employs a graph based approach. This framework is suitable for non-experts as it does not require the specification of the provenance in its entirety or an understanding of its structure. We show promising initial experimental results of our approach.
