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Group recommender systems suggest items of interest to a group of people. Traditionally, group recommenders provide recommendations by aggregation the group membersâ preferences. Nowadays, there is a trend of decentralized group recommendation process th ...
Because of the abundance of news on the web, news recommendation is an important problem. We compare three approaches for personalized news recommendation: collaborative filtering at the level of news items, content-based system recommending items with sim ...
The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...
The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...
