论文标题
天际线操作员和后悔的最小化技术，用于在查询过程中管理用户偏好
Skyline Operators and Regret Minimization Techniques for Managing User Preferences in the Query Process
论文作者
论文摘要
从数据集中选择最具代表性的元组的问题导致了强大的工具的开发，其中天际线和排名（或TOP-K）查询在这些问题中脱颖而出，因为它们能够支持在查询过程中优化多个标准的能力。本文调查了在扩展上述工具以克服其局限性方面所做的杰出努力，分别是产出结果的爆炸和查询表达的困难。此外，我们探讨了这些最新技术作为基于首选项的查询框架的应用，提出了对其查询个性化功能的比较，可以控制输出大小的能力以及相对于用户输入偏好的灵活性。
The problem of selecting the most representative tuples from a dataset has led to the development of powerful tools, among which Skyline and Ranking (or Top-k) queries stand out for their ability to support the optimization of multiple criteria in the query process. This paper surveys the remarkable efforts made towards the extension of the aforementioned tools to overcome their limitations, respectively the explosion of the output result and the difficulty of query formulation. Moreover, we explore the application of these state-of-the-art techniques as preference-based query frameworks, proposing a comparison of their query personalization capabilities, the ability to control the output size and their flexibility with respect to the user input preferences.
