  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.
