In this paper, we propose a personalized re-ranking algorithm through mining user dwell times captured from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser and then infer concept word level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. To reveal the advantage of our proposed personalized re-ranking algorithm, we compare the rankings produced by our algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results show the superiority of our method.