Relational algebra for multi-ranked similarity-based databases

R. Belohlávek, Vilém Vychodil
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引用次数: 3

Abstract

We present multi-ranked relational model of data which extends the classic Codd's model by considering similarity relations on domains and ranks assigned to values of tuples. The ranks represent degrees to which values in tuples match similarity-based queries. Unlike various single-ranked similarity-based database models where ranks are assigned to whole tuples, in the present model the ranks are assigned to tuple values. As a consequence, the multi-ranked model allows users to directly observe how values in tuples contribute to results of similarity-based queries. We present foundations of the model, relational operations and relational algebra as the primary query language, and its relationship to single-ranked models which have been used in the past. We argue that the multi-ranked model is more suitable for applications in which data analysts require a finer view on results of queries than in the single-ranked model.
基于多级相似度数据库的关系代数
在经典Codd模型的基础上,考虑了元组值在域和秩上的相似关系,提出了数据的多秩关系模型。排名表示元组中的值与基于相似性的查询匹配的程度。不同于各种基于相似性的单排名数据库模型,其中排名分配给整个元组,在当前模型中,排名分配给元组值。因此,多排序模型允许用户直接观察元组中的值如何影响基于相似性的查询结果。我们提出了模型的基础,关系运算和关系代数作为主要的查询语言,以及它与过去使用的单级模型的关系。我们认为,与单级模型相比,多级模型更适合于数据分析师需要更精细地查看查询结果的应用程序。
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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