With the development of the Internet and e-commerce, users can write their opinions about the product on the website after they buy it or use it. There are a large number of product reviews contain abundant information which can help manufacturers and users to make important decisions. Based on semantic and linguistic analysis, this paper proposes a method which can extract product features from the online reviews and rank them based on customer attention strength. At the same time, the sentiment orientation users have on the feature is determined according to the polarity scores of opinion words. The online reviews about notebook Computers are used as experimental data. Experimental results show that the method achieved good precision and recall rate.