Machine learningRanking models
排序聚合方法
排序聚合是一系列方法，旨在将多个备选方案的排序列表合并为一个共识排序。Dwork、Kumar、Naor和Sivakumar（2001）在网络搜索背景下对这些方法进行了形式化研究，它们解决了如何综合来自多个来源（如搜索引擎、专家评委或选票）的不同偏好排序，形成一个连贯的、有代表性的排序，从而最大限度地减少输入排序之间的总体分歧。
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来源
- Dwork, C., Kumar, R., Naor, M., & Sivakumar, D. (2001). Rank aggregation methods for the web. Proceedings of the 10th International Conference on World Wide Web, 613–622. DOI: 10.1145/371920.372165 ↗
如何引用本页
ScholarGate. (2026, June 2). Rank Aggregation Methods. ScholarGate. https://scholargate.app/zh/decision-making/rank-aggregation
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