The paper presents a new method of discovering relevant contextual information from the user-generated reviews in order to provide better recommendations to the users when such reviews complement traditional ratings used in recommender systems. In particular, we classify all the user reviews into the "context rich" specific and "context poor" generic reviews and present a word-based and an LDA-based methods of extracting contextual information from the specific reviews. We also show empirically

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... on the Yelp data that, collectively, these two methods extract almost all the relevant contextual information across three di↵erent applications and that they are complementary to each other: when one method misses certain contextual information, the other one extracts it from the reviews.