论文标题
部分可观测时空混沌系统的无模型预测
Flexible skyline: overview and applicability
论文作者
论文摘要
排名（或顶级K）和天际线查询是从大数据集中提取有趣数据的最流行方法。第一个是基于评估和对元素进行评分函数的基础。它的计算很快，但是对评估函数的选择很敏感。天际线查询基于主导地位，结果是所有非主导元素的集合。这是一种非常有趣的方法，但是它不能控制输出的基数。最近的研究发现了更多的技术来弥补这些缺点。特别是，本文将重点介绍灵活的天际线方法。
Ranking (or top-k) and skyline queries are the most popular approaches used to extract interesting data from large datasets. The first one is based on a scoring function to evaluate and rank tuples. Its computation is fast, but it is sensitive to the choice of the evaluating function. Skyline queries are based on the idea of dominance and the result is the set of all non-dominated tuples. This is a very interesting approach, but it can't allow to control the cardinality of the output. Recent researches discovered more techniques to compensate for these drawbacks. In particular, this paper will focus on the flexible skyline approach.
