论文标题
给出正确的答案：有关如何扩展排名和天际线查询的简要概述
Giving the Right Answer: a Brief Overview on How to Extend Ranking and Skyline Queries
论文作者
论文摘要
为了检索数据库中的最佳结果，我们使用Top-K查询和天际线查询，但出现了一些问题。 FORERS过于依赖用户偏好，这些用户偏好很难量化，并且可能偏向数据的获取，而后者倾向于输出过多的数据。在本文中，我们探讨了三个不同的研究分支，这些研究旨在克服这种局限性：灵活/受限的天际线，天际线订购/排名以及遗憾的最小化。我们分析了它们的工作方式，并进行了比较，以指导读者选择最适合其用例的方法。
To retrieve the best results in a database we use Top-K queries and Skyline queries but some problems arise. The formers rely too much on user preferences, which are difficult to quantify and may skew the fetching of the data, while the latters tend to output too much data. In this paper, we explore three different branches of research that seek to overcome such limitations: Flexible/Restricted Skylines, Skyline Ordering/Ranking, and Regret Minimization. We analyze how they work and we make comparisons among them to guide the reader to choose the approach that best fits their use cases.
