Charles-Emmanuel Dias

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Recommender systems were developed to cherry-pick interesting content in an always growing environment to help users discover new products or information that they might like. Traditional collaborative filtering methods mainly focus on the ratings to establish user profiles, ignoring the joint review text. Our work does the opposite. We use the written(More)
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