Automatic opinion mining and summarization from online reviews are very useful for customers and merchants. This paper proposes a method to extract opinions from Chinese product reviews. Firstly, reviews are pre-processed and the sentiment features are extracted based on a sentiment lexicon. Then, it finds out the matching target attribute using the extracted sentiment features base on the using co-occurrence knowledge of topic feature and sentiment feature. After the opinions were found, it generates the summary for products according to the most common opinions.