291 citations · 555 across the 3 of their papers we have counts for
3 papers
cs.IR2018★ 238 cited
MMALFM: Explainable Recommendation by Leveraging Reviews and Images
Zhiyong Cheng, Xiaojun Chang, Lei Zhu +2
Although the latent factor model achieves good accuracy in rating prediction, it suffers from many problems including cold-start, non-transparency, and suboptimal results for indiv…
cs.IR2017★ 26 cited
Explainable Entity-based Recommendations with Knowledge Graphs
Rose Catherine, Kathryn Mazaitis, Maxine Eskenazi +1
Explainable recommendation is an important task. Many methods have been proposed which generate explanations from the content and reviews written for items. When review text is una…
cs.IR2017★ 291 cited
TransNets: Learning to Transform for Recommendation
Rose Catherine, William Cohen
Recently, deep learning methods have been shown to improve the performance of recommender systems over traditional methods, especially when review text is available. For example, a…