Expanding Controllability of Hybrid Recommender Systems: From Positive to Negative Relevance

Rahdari, Behnam (University of Pittsburgh) | Tsai, Chun-Hua (University of Pittsburgh) | Brusilovsky, Peter (University of Pittsburgh)

AAAI Conferences 

For example, while a recommendation of their behavior such as browsing trails, bookmarks ratings, source based on co-authorship links ranks attendees or created social links. It enables modern recommender systems by its social similarity with the target user, the recommendation to use multiple sources of information about user interests case might require to find attendees who are interested and preferences to deliver better recommendations. This in similar topics while being most likely unknown is most frequently done using parallel hybrid recommendation to the target user (i.e., having the weakest social similarity).

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