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Concepts identification of an NL query in NLIDB systems

机译:NLIDB系统中NL查询的概念识别

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This paper proposes a novel approach to capture the concept of an NL query. Given an NL query, the query is mapped to a tagset, which carries the concepts information. The tagset was created by mapping every noun chunk to the attribute of a table (tableName.attributeNarne) and every verb chunk to a relation in the ER schema. The approach is discussed using the Courses Management domain of a University and can be extended to other domains. The tagset here was formed using the ER-schema of the Courses Management Portal of our university. We used the statistical approach to identify the concepts. We ourselves formed a tagged corpus with different types of NL queries. Conditional Random Field algorithm was used for the classification. The results are very promising and are compared to the rule based approach seen in Gupta et al. (2012) [1].
机译:本文提出了一种新颖的方法来捕获NL查询的概念。给定NL查询,该查询将映射到一个标签集,该标签集携带概念信息。通过将每个名词块映射到表的属性(tableName.attributeNarne)并将每个动词块映射到ER模式中的关系来创建标记集。该方法是使用大学的“课程管理”领域进行讨论的,可以扩展到其他领域。这里的标签集是使用我们大学课程管理门户的ER模式形成的。我们使用统计方法来识别概念。我们自己用不同类型的NL查询组成了带标记的语料库。使用条件随机场算法进行分类。结果是非常有希望的,并与Gupta等人的基于规则的方法进行了比较。 (2012)[1]。

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