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Nowadays, Customer's product reviews can be widely found on the Web, be it in personal blogs, forums, or ecommerce websites. They contain important products' in-forma�on and therefore became a new data source for compe��ve intelligence. �n that account, these reviews need to be analyzed and summarized in order to help the leader of an en�ty (company, brand, etc.) to make appropriate decisions in an e�ec�ve way. �owever, most previous review summariza�on studies focus on summarizing sen�ment distribu�on toward di�erent product features without taking into account that the real advantages and disadvantages of a product clarify over �me. For this reason, in this work we aim to propose a new system for product opinion summariza�on which depends on the �me when reviews are e�pressed and that covers the sen�ments change about product features. The proposed system firstly, generates a summary based on product features in order to give more accurate and efficient informa�on about di�erent features. �econdly, classify the product based on its features in its appropriate class (good, medium or bad product) using a fuzzy logic system. The e�perimental results demonstrate the e�ec�veness of the proposed system to generate the real image of a product and its features in reviews.

No abstract