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Coverage, Redundancy and Size-Awareness in Genre Diversity for Recommender Systems
Saúl Vargas, Linas Baltrunas, Alexandros Karatzoglou, Pablo Castells
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diversity, recommendation system, coverage
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Accuracy and Diversity in Cross-domain Recommendations for Cold-start Users with Positive-only Feedback
Ignacio Fernández-Tobías, Paolo Tomeo, Iván Cantador, Tommaso Di Noia, Eugenio Di Sciascio
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diversity, recommendation system, cold-start
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Fusing Diversity in Recommendations in Heterogeneous Information Networks
Sharad Nandanwar, Aayush Moroney, M. N. Murty
Machine Learning, Recommendation
diversity, recommendation system, heterogeneous information networks
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Personalized Entity Recommendation: A Heterogeneous Information Network Approach
Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, Jiawei Han
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recommendation system, heterogeneous information networks, collaborative filtering, matrix factorization
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Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity
Tien T. Nguyen, Pik-Mai Hui, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan
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diversity, recommendation system, filter bubbles
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A Network-centric Framework for Auditing Recommendation Systems
Abhisek Dash, Animesh Mukherjee, Saptarshi Ghosh
Data mining, Recommendation
graph, diversity, recommendation system
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Deep Neural Networks for YouTube Recommendations
Paul Covington, Jay Adams, Emre Sargin
Machine Learning, Recommendation
deep learning, recommendation system