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Online user comments are an important data asset on e-commerce sites and have a great potential value for online users and merchants. However, accurate and effective extraction of the characteristics of products and users\u2019 sentiment evaluation from a tremendous amount of comments is a significant challenge. Based on the concept of the LinLog energy model, this paper proposes an online review attribute-sentiment pair correlation model that evaluates user comments. After preprocessing the comment data of mobile phones and constructing an attribute dictionary, the proposed model conducts a clustering analysis of attributes and sentiment pairs to gain accurate assessment of attributes in order to explore potential information from user comments. 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