论文标题
试图弥合天际线和顶级查询之间的差距
Trying to bridge the gap between skyline and top-k queries
论文作者
论文摘要
有两个最常见的范例用于识别多目标设置中的首选项记录，一个范围依赖于主导地位，例如Skyline Operation，而另一个则基于在记录的属性上定义的效用函数，通常使用TOP-K查询。尽管它们非常受欢迎，但我们必须考虑到他们的主要缺点，这使我们描述了三个硬性要求：个性化，可控的产出尺寸和优先规范的灵活性。实际上，天际线查询很容易指定，但它们没有配备任何能够容纳用户首选项或控制结果集的基数的方法。取而代之的是，排名查询是一个特定的评分函数来对元组进行排名，并且可以轻松控制输出大小，但是很难正确指定此评分功能的权重，以便对属性具有不同的重要性。在本文中，我们描述了三种不同的方法，这些方法试图满足上面提到的三个硬性要求，即具有天际线查询或排名查询的优势。这些方法是：灵活的天际线，Ord-Oru和UTK。
There are two most common paradigms that are used in order to identify records of preference in a multi-objective settings, one relies on dominance, like the skyline operator, the other instead, on a utility function defined over the records' attributes, typically using top-k queries. Although they are very popular, we have to take in account their main disadvantages, which bring us to describe three hard requirements: personalization, controllable output size, and flexibility in preference specification. In fact Skyline queries are simple to specify but they are not equipped with any means to accommodate user preferences or to control the cardinality of the result set. Ranking queries adopt, instead, a specific scoring function to rank tuples, and can easily control the output size, but it is difficult to specify correctly the weights of this scoring function in order to give different importance to the attributes. In this paper we describe three different approaches which try to satisfy the three hard requirements mentioned above embracing the advantages either of the Skyline queries or of the ranking queries. These approaches are namely: Flexible Skyline, ORD-ORU and UTK.
