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Explainable recommendation is an important task.
Explaining collaborative filtering recommendations.. In CSCW
J. Herlocker, J. Konstan, and J. Riedl. 2000 · 2000
Earlier work this paper cites.
Explaining Recommendations: Satisfaction vs. Promotion. In Beyond Personalization Workshop
Mustafa Bilgic and Raymond J. Mooney. 2005 · 2005
Earlier work this paper cites.
Designing and Evaluating Explanations for Recommender Systems
N. Tintarev and J. Masthoff. 2011 · 2011
Cited alongside, same era.
Do Social Explanations Work?: Studying and Modeling the Effects of Social Explanations in Recommender Systems. In WWW ’13
A. Sharma and D. Cosley. 2013 · 2013
Cited alongside, same era.
An Entity Graph Based Recommender System. In RecSys ’16 Posters
S. Chaudhari, A. Azaria, and T. Mitchell
Cited in the paper.
Hidden Factors and Hidden Topics: Understanding Rating Dimensions with Review Text. In RecSys ’13
J. McAuley and J. Leskovec
Cited in the paper.
Top-N Recommendations from Implicit Feedback Leveraging Linked Open Data. In RecSys ’13
V. Ostuni, T. Di Noia, E. Di Sciascio, and R. Mirizzi
Cited in the paper.
InMind Movie Agent - A Platform for Research (In Preparation)
F. Pecune, T. Baumann, Y. Matsuyama, O. Romero, S. Akoju, Y. Du, R. Catherine, J. Cassell, M. Eskenazi, A. Black, and W. Cohen
Cited in the paper.
Trust Building with Explanation Interfaces. In IUI ’06
P. Pu and L. Chen
Cited in the paper.
Tagsplanations: Explaining Recommendations Using Tags. In IUI ’09
J. Vig, S. Sen, and J. Riedl
Cited in the paper.
Programming with Personalized Pagerank: A Locally Groundable First-order Probabilistic Logic. In Proc. CIKM ’13
W. Wang, K. Mazaitis, and W. Cohen
Cited in the paper.
Personalized Entity Recommendation: A Heterogeneous Information Network Approach. In WSDM ’14
X. Yu, X. Ren, Y. Sun, Q. Gu, B. Sturt, U. Khandelwal, B. Norick, and J. Han
Cited in the paper.
Explicit Factor Models for Explainable Recommendation Based on Phrase-level Sentiment Analysis. In SIGIR ’14
Y. Zhang, G. Lai, M. Zhang, Y. Zhang, Y. Liu, and S. Ma
Cited in the paper.
Automatic Selection of Linked Open Data features in Graph-based Recommender Systems. In CBRecSys 2015
C. Musto, P. Basile, M. de Gemmis, P. Lops, G. Semeraro, and S. Rutigliano · 2015
Later among the works it cites.
Personalized Recommendations Using Knowledge Graphs: A Probabilistic Logic Programming Approach. In Proc. RecSys ’16
R. Catherine and W. Cohen. 2016 · 2016
Later among the works it cites.
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