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Motif Enhanced Recommendation over Heterogeneous Information Network
Huan Zhao, Yingqi Zhou, Yangqiu Song, Dik Lun Lee
Machine Learning, Recommendation
diversity, heterogeneous information networks
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Diversity in recommender systems – A survey
Matevz Kunaver, Tomaz Pozrl
Machine Learning, Recommendation
diversity
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Coverage, Redundancy and Size-Awareness in Genre Diversity for Recommender Systems
Saúl Vargas, Linas Baltrunas, Alexandros Karatzoglou, Pablo Castells
Recommendation
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
Recommendation
diversity, recommendation system, cold-start
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Filter bubbles, echo chambers, and online news consumption
Seth Flaxman, Sharad Goel, Justin M. Rao
Social network
diversity, news consumption, echo chambers, filter bubbles
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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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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
Recommendation
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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Interesting Pattern Mining in Multi-Relational Data
Eirini Spyropoulou, Tijl De Bie, Mario Boley
Data mining
diversity, pattern mining, multi-relational data, K-partite graphs
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Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
Machine Learning
AI, machine learning, diversity