7 citations · 8 across the 5 of their papers we have counts for
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cs.IR2020★ 1 cited
User Profiling from Reviews for Accurate Time-Based Recommendations
Oznur Alkan, Elizabeth Daly
Recommender systems are a valuable way to engage users in a system, increase participation and show them resources they may not have found otherwise. One significant challenge is t…
cs.IR2019
IRF: Interactive Recommendation through Dialogue
Oznur Alkan, Massimiliano Mattetti, Elizabeth M. Daly +2
Recent research focuses beyond recommendation accuracy, towards human factors that influence the acceptance of recommendations, such as user satisfaction, trust, transparency and s…
cs.IR2019
An Evaluation Framework for Interactive Recommender System
Oznur Alkan, Elizabeth M. Daly, Adi Botea
Traditional recommender systems present a relatively static list of recommendations to a user where the feedback is typically limited to an accept/reject or a rating model. However…