Ranking search intents underlying a query

Observation on query log of search engine indicates that queries are usually ambiguous. Similar to document ranking, search intents should be ranked to facilitate information search. Previous work attempts to rank intents with merely relevance score. We argue that diversity is also important. In this work, unified models are proposed to rank intents underlying a query by combining relevance score and diversity degree, in which the latter is reflected by non-overlapping ratio of every intent and aggregated non-overlapping ratio of a set of intents. Three conclusions are drawn according to the experiment results. Firstly, diversity plays an important role in intent ranking. Secondly, URL is more effective than similarity in detecting unique subtopics. Thirdly, the aggregated non-overlapping ratio makes some contribution in similarity based intent ranking but little in URL based intent ranking.