In this article, we propose a method for finding active experts for a new question in order to improve the effectiveness of a question routing process. By active expert for a given question, we mean those experts who are active during the time of its posting. The proposed method uses the query likelihood language model, and two new measures, activeness and answering intensity. We compare the performance of the proposed method with its baseline query likelihood language model. We use a real-world dataset, called History, downloaded from Yahoo! Answers web portal for this purpose. In every comparing scenario, the proposed method is found to outperform the corresponding baseline model.