用户的点击行为会受到用户的浏览行为、周围文档的特征等因素的影响，故在分析用户点击日志时不能直接将用户点击解释为文档相关性．为了更加准确地获得文档的相关性特征，文中提出了基于用户浏览时间的点击模型．假设文档原文的相关性会影响用户浏览该文档原文的时间，即文档越相关用户浏览文档的耗时越长，这样便可利用用户浏览文档的时间来推测文档的相关程度; 经过分析，确定使用指数分布来描述浏览时间; 最后通过实验验证了该模型的有效性．结果表明，所提出的模型能够比较好地估计文档的相关性，更加准确地预测用户的点击情况，其性能优于现有的点击模型．

As the clicks of users are affected by many factors such as the browsing behaviors of users and the features of adjacent documents,they cannot be directly interpreted as document relevance during the analysis of users' click log. In order to obtain correct document relevance features,a click model based on browsing time is proposed. In this model,the document relevance is assumed to affect the browsing time for the document,which means a user may spend more browsing time if the document is more likely to be relevant. Therefore,the document relevance can be estimated according to the browsing time. Then,an exponential distribution is determined to describe users' browsing time,and some experiments are carried out to verify the effectiveness of the proposed model. The results indicate that the model is superior to the existing click models because it can estimate document relevance and future clicks more accurately.