在竞争性搜索中引入结果多样性，缓解作者模仿热门内容的恶性循环。
Search results diversification in competitive search
- 设计融合多样性机制的排序算法，打破仅依赖相关性的传统模式。
- 理论与实证证明，多样性排序能实现稳定的平衡状态。
- 适合关注搜索引擎公平性与内容生态健康的从业者与研究者。
在网页检索中，网页作者常有动机使其内容在相关查询中获得高排名，因此网络环境是典型的竞争性搜索场景。以往研究主要关注仅基于相关性评估的排序函数。本文研究整合结果多样性的排序方法，证明在多样性排序的竞争性搜索设置中存在均衡。此外，理论和实证均表明，当应用结果多样化时，作者过去模仿高排名文档内容的现象会显著减弱。
原文摘要 · Abstract (English)
In Web retrieval, there are many cases of competition between authors of Web documents: their incentive is to have their documents highly ranked for queries of interest. As such, the Web is a prominent example of a competitive search setting. Past work on competitive search focused on ranking functions based solely on relevance estimation. We study ranking functions that integrate a results-diversification aspect. We show that the competitive search setting with diversity-based ranking has an equilibrium. Furthermore, we theoretically and empirically show that the phenomenon of authors mimicking content in documents highly ranked in the past, which was demonstrated in previous work, is mitigated when search results diversification is applied.
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