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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 empiricallydblp:conf/recsys/BaumanT14 fatcat:gvxqfsdourdwxdxe4xycts2zqq