1. In a computing environment, a method executed at least in part on at least one processor, comprising: receiving a query; extracting features related to the query that comprise a context feature set, and a frequency feature set, the context feature set comprising textual context-related features of query keyword data in news items, the frequency feature set comprising keyword frequency data in the news items; using the features to estimate whether the query is a news-related query, including by providing the features to a classifier that is built by referencing data that corresponds to news items updated within a preset time period with at least one data source that has not been updated within the preset time period, and by detecting temporal changes associated with the data that corresponds to news items updated within the preset time period; receiving classification output corresponding to a predicted click-through rate from the classifier; estimating from the classification output whether the query is a news-related query; and outputting results based at least in part on the estimate of whether the query is news-related.
5. The method of claim 1 further comprising obtaining the data that corresponds to the news items updated within the preset time period by accessing at least one data store comprising a corpus of events crawled from news sources.