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Relevant question retrieval and ranking is a typical task in community question answering (CQA). Existing methods mainly focus on long and syntactically structured queries. However, when an input query is short, the task becomes challenging, due to a lack information regarding user intent. In this paper, we mine different types of user intent from various sources for short queries. With these intent signals, we propose a new intent-based language model. The model takes advantage of bothdoi:10.1145/2556195.2556239 dblp:conf/wsdm/WuWZCDS14 fatcat:qcgoeb3ulbdgvlyvcd3tonlapi