基于关联的查询松弛,用于基于示例的对话建模

Cheongjae Lee, Sungjin Lee, Sangkeun Jung, Kyungduk Kim, Donghyeon Lee, G. G. Lee
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引用次数: 13

摘要

查询松弛是指在搜索数据库时,如果查询没有返回结果,则减少查询上的约束数量的过程。这是一个重要的过程,可以提取适当数量的查询结果,因为过于严格约束的查询可能不返回任何结果,而过于松散约束的查询可能返回太多结果。提出了一种基于关联的查询松弛(CBQR)方法来选择合适的约束子集。使用基于示例的对话框建模框架来验证我们的算法。初步结果表明,该方法有利于查询松弛的自动化。我们认为CBQR算法有效地放宽了对失败查询的约束,以返回更多的对话示例。
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Correlation-based query relaxation for example-based dialog modeling
Query relaxation refers to the process of reducing the number of constraints on a query if it returns no result when searching a database. This is an important process to enable extraction of an appropriate number of query results because queries that are too strictly constrained may return no result, whereas queries that are too loosely constrained may return too many results. This paper proposes an automated method of correlation-based query relaxation (CBQR) to select an appropriate constraint subset. The example-based dialog modeling framework was used to validate our algorithm. Preliminary results show that the proposed method facilitates the automation of query relaxation. We believe that the CBQR algorithm effectively relaxes constraints on failed queries to return more dialog examples.
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