In this paper, we design and develop a web service for movie rating and review summarization. In feature-based summarization, we propose a new approach based on LSA to collect product features. Furthermore, we find a way to reduce the size of summary based on the product features obtained from LSA. SVM is adopted to perform sentiment analysis and the rating information is derived from the classification result. Meanwhile, we consider system response time to design the system and the whole system can be extended to other product review domains with a little modification.