CCCFNet: a content-boosted collaborative filtering neural network for cross domain recommender systems - Lian, Jianxun; Zhang, Fuzheng; Xie, Xing; Sun, Guangzhong (International Conference on World Wide Web (WWW'17 Companion), 2017)
To overcome data sparsity problem, we propose a cross domain recommendation system named CCCFNet which can combine collaborative filtering and content-based filtering in a unified framework. We first introduce a factorization framework to tie CF and content-based filtering together. Then we find that the MAP estimation of this framework can be embedded into a multi-view neural network. Through this neural network embedding the framework can be further extended by advanced deep learning techniques.