Mining approximate functional dependencies and concept similarities to answer imprecise queries

Ullas Nambiar, S. Kambhampati
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引用次数: 56

Abstract

Current approaches for answering queries with imprecise constraints require users to provide distance metrics and importance measures for attributes of interest. In this paper we focus on providing a domain and end-user independent solution for supporting imprecise queries over Web databases without affecting the underlying database. We propose a query processing framework that integrates techniques from IR and database research to efficiently determine answers for imprecise queries. We mine and use approximate functional dependencies between attributes to create precise queries having tuples relevant to the given imprecise query. An approach to automatically estimate the semantic distances between values of categorical attributes is also proposed. We provide preliminary results showing the utility of our approach.
挖掘近似的功能依赖关系和概念相似性来回答不精确的查询
当前回答带有不精确约束的查询的方法要求用户提供感兴趣属性的距离度量和重要性度量。在本文中,我们专注于提供一个独立于域和最终用户的解决方案,以支持对Web数据库的不精确查询,而不会影响底层数据库。我们提出了一个查询处理框架,该框架集成了IR和数据库研究的技术,可以有效地确定不精确查询的答案。我们挖掘并使用属性之间的近似功能依赖关系来创建具有与给定的不精确查询相关的元组的精确查询。提出了一种自动估计分类属性值之间语义距离的方法。我们提供的初步结果显示了我们的方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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