1. A method, implemented on at least one machine having at least one processor, storage, and a communication platform connected to a network for ranking a search result, comprising: accessing, by the at least one machine, a set of recency ranking data comprising one or more past search queries, one or more past search results, and one or more recency features, wherein the recency features comprise: a time-sensitive feature representing a particular time period that was determined based on content of at least some of the past search queries, wherein the at least some of the past search queries were sensitive to the particular time period, and a query timestamp feature representing the time at which the past search queries were received at a search engine; training, by the at least one machine, a first ranking model via machine learning based on the recency features; and determining when recency is to be utilized for ranking a search result based on the ranking model.