1. A method, comprising: accessing, by one or more computer systems, a set of recency ranking data comprising one or more recency search queries and one or more recency search results, each of the recency search queries being recency-sensitive with respect to a particular time period and being associated with a query timestamp representing the time at which the recency search query is received at a search engine, each of the recency search results being generated by the search engine for one of the recency search queries and comprising one or more recency network resources; constructing, by the one or more computer systems, a plurality of recency features from the set of recency ranking data; and training, by the one or more computer systems, a first ranking model via machine learning using at least the recency features.