… In this section, we introduce the proposed deep social collaborative fltering framework
DSCF. As discussed earlier, to exploit social networks for recommendations, we need to (a) …

… , which combine collaborative filtering and auxiliary information such as social network …
of collaborative filtering and deep learning, we propose a Deep Trust Recommender (DTR) …

… collaborative denoising autoencoder (CDAE) [28] is proposed to develop the user’s preferable
zones with implicit feedback. Neural collaborative filtering … deep collaborative filtering. The …

… We first brief the general framework for item-based collaborative filtering. We then discuss
… Since the work focuses on the pure collaborative filtering setting, we leave the incorporation …

… In this research, authors conduct a systematic review focusing on state-of-the-art literature
on deep learning techniques applied in collaborative filtering recommendation, and also …

… In this paper a solution integrating deep learning and collaborative filtering approach is
proposed to address these limitations and largely improve recommendation performance for CS …

… models based on deep learning have been proposed… collaborative filtering with deep
learning. In this work, we propose a novel multi-criteria collaborative filtering model based on deep …

… shallow collaborative and complex deep … a deep neural model named collaborative neural
social recommendation (CNSR), which jointly incorporates the unique characteristic of social …

… vectors to a deep neural framework, to capture their non-linear correlations. Finally, we
formulate the objective function of our geo-based deep collaborative filtering model (GeoDCF) as …

… Abstract—Recommender systems (RS) are used by many social networking applications
and online e-commercial services. Collaborative filtering (CF) is one of the most popular …