2. The method of claim 1 , further comprising: accessing, by the at least one machine, a plurality of first search queries and a plurality of first search results, each of the first search results being generated by the search engine for one of the first search queries and comprising one or more first network resources; and for each of the first search queries, by the at least one machine, automatically determining whether the first search query is sensitive with respect to a first time period during which the first search query is received at the search engine; and if the first search query is sensitive, then including the first search query and the first search result generated for the first search query in the set of recency ranking data.
2. The method of claim 1 , further comprising: accessing, by the at least one machine, a plurality of first search queries and a plurality of first search results, each of the first search results being generated by the search engine for one of the first search queries and comprising one or more first network resources; and for each of the first search queries, by the at least one machine, automatically determining whether the first search query is sensitive with respect to a first time period during which the first search query is received at the search engine; and if the first search query is sensitive, then including the first search query and the first search result generated for the first search query in the set of recency ranking data. 3. The method of claim 2 , wherein automatically determining whether a current search query is sensitive with respect to a current time period during which the current search query is received at the search engine comprises: defining one or more reference time periods for the current time period, each of the reference time periods being prior to the current time period; constructing one or more current language models for the current time period, each of the current language models representing a particular type of search-related activity occurring during the current time period; constructing one or more reference language models for each of the reference time periods, each of the reference language models corresponding to one of the current language models and representing the particular type of search-related activity represented by the corresponding current language model occurring during the corresponding reference time period; computing a score for the current search query that represents a difference between the current search query's affinity to the current language models for the current time period and the current search query's affinity to the reference language models for each of the reference time periods; and if the score satisfies a predetermined threshold requirement, then classifying the current search query as sensitive with respect to the current time period.