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AbstractWith the constant increase in the amount of information available in online communities, the task of building an appropriate Recommender System to support the user in her decision making process …...

Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. How- ever, recent studies in this direction only con- sider direct …...

Recommendation systems (RS) take advan- tage of products and users information in order to propose items to consumers. Collaborative, content-based and a few hybrid RS have been developed in the …...

Product review mining is an important task that can benefit both businesses and con- sumers. Lately a number of models com- bining collaborative filtering and content analysis to model reviews …...

AbstractIn this paper, we propose an approach to learn distributed representations of users and items from text comments for recommendation systems. Traditional recommendation algorithms, e.g. collaborative filtering and matrix completion, …...

AbstractA common step in developing an understanding of a vertical domain, e.g. shopping, dining, movies, medicine, etc., is curating a taxonomy of categories specific to the domain. These human created …...

AbstractThis study evaluates whether model-based Collaborative Filtering (CF) algorithms, which have been extensively studied and widely used to build recommender systems, can be used to predict which common nouns a …...