论文标题
灵活的天际线：一个查询所有统治它们的问题
Flexible Skyline: one query to rule them all
论文作者
论文摘要
在大型数据集中识别相关信息并根据某些偏好或用户标准找到最佳信息的最常见原型是Top-K查询（基于记录属性上定义的基于Records属性的ONA分数函数）和Skyline查询（基于Pareto Promite oftplass Tublame oftplace）。尽管它们扩散了很大，但两种方法都有其利弊。在本调查文件中，这些方法与灵活的天际线进行了比较，这是一个框架，该框架使用新颖的概念off-dominanceto组合了排名和天际线方法。
The most common archetypes to identify relevant information in large datasets and find the bestoptions according to some preferences or user criteria, are the top-k queries (ranking method based ona score function defined over the records attributes) and skyline queries (based on Pareto dominance oftuples). Despite their large diffusion, both approaches have their pros and cons. In this survey paper, a comparison is made between these methods and the Flexible Skylines, which is a framework that combines the ranking and skyline approaches using the novel concept ofF-dominanceto a set of monotone scoring function F.
