A Survey on Recommender Systems for News Data

The advent of online newspapers broadened the diversity of available news’ sources. As the volume of news grows, so does the need for tools which act as filters, delivering only information that can be considered relevant to the reader. Recommender systems can be used in the organization of news, easing reading and navigation through newspapers. Employing the users’ history on items consumption, user profiles or other source of knowledge, these systems can personalize the user experience, reducing the information overload we currently face. This chapter presents these recommender filters, explaining their particularities and applications in the news’ domain.

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