Convolutional Matrix Factorization for Recommendation Explanation

Yichao Lu, Ruihai Dong, Barry Smyth

Abstract: In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.