Quality-Aware Movie Recommendation System on Big Data
Yan Tang, Mingzheng Li, Wangsong Wang, Pengcheng Xuan, Kun Geng · 2017
The movie recommendation is one of the most active application domain for recommendation systems (RS). However, with the rapid growth in the number of films, users have vastly different needs for the quality of the movie. In addition, facing big data, the traditional stand-alone RS is incapable to meet the need of an accurate and prompt recommendation. Aiming at solving these challenges, in this paper, we first parallelize the collaborative filtering to improve the computational efficiency, then we propose a quality-aware big data based movie recommendation system.