In this paper, we propose a web search retrieval approach which automatically detects recency sensitive queries and increases the freshness of the ordinary document ranking by a degree proportional to the probability of the need in recent content. We propose to solve the recency ranking problem by using result diversification principles and deal with the query's non-topical ambiguity appearing when the need in recent content can be detected only with uncertainty. Our offline and online experiments with millions of queries from real search engine users demonstrate the significant increase in satisfaction of users presented with a search result generated by our approach.

翻译：本文提出一种网络搜索检索方法，该方法能自动检测时效敏感查询，并以与近期内容需求概率成比例的程度提升普通文档排序的新鲜度。我们提出利用结果多样化原则解决时效性排序问题，并处理当近期内容需求仅能以不确定性方式检测时出现的查询非主题歧义问题。基于真实搜索引擎用户数百万查询的离线与在线实验表明，采用本文方法生成的搜索结果能显著提升用户满意度。