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Towards an interface for translating natural language questions to SQL: a conceptual framework from a systematic review

机译:朝着用于将自然语言问题翻译为SQL的界面:来自系统评审的概念框架

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摘要

Querying relational databases using human language is a complex process that must take into consideration the lack of knowledge of SQL by the end users who use the content of these systems. Many studies published in the last decade are based on limited, unbalanced or even small datasets, thing that is by far not realistic for training and evaluating a model. The SQL structure is rich and the scale of complexity is very large. Moreover, the difference between the natural language, which is a language of communication, and the SQL language that contains details of implementation specific to relational databases, adds more complications to the problem. In this paper, we present a full systematic review of the existing approaches in the task of text to SQL and we introduce the details of our suggested architecture as well as our new approach to tackle the problem of nested queries.
机译:使用人类语言查询关系数据库是一种复杂的过程,必须考虑使用这些系统内容的最终用户缺乏对SQL的知识。在过去十年中发表的许多研究是基于有限的,不平衡甚至小的数据集,这是训练和评估模型的最重要的东西。 SQL结构丰富,复杂程度非常大。此外,自然语言之间的差异是通信语言,以及包含特定于关系数据库的实现细节的SQL语言,对问题增加了更多的复杂性。在本文中,我们对文本任务的现有方法进行了全面的系统审查,我们介绍了我们建议的架构的详细信息以及我们解决嵌套查询问题的新方法。

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