DeepMovRS: A unified framework for deep learning-based movie recommender systems

摘要

A novel unified framework for deep learning-based movie recommender systems, DeepMovRS, is proposed. The proposed framework accepts various heterogeneous inputs from user and item communities knowledge to explicit and implicit feedbacks. To unify deep architecture of the framework for retrieving and ranking items, it uses suitable machine learning tools to improve the quality of recommendations. The proposed framework is flexible and modular, and it can be generalized and distributed easily, so it can be a rational choice for commercial movie recommender systems.