Spatial-Temporal Recommendation for On-demand Cinemas

Taofeng Xue, Beihong Jin, Beibei Li, Kunchi Liu, Qi Zhang, Sihua Tian

Abstract: The on-demand cinema is an emerging offline entertainment venue, guiding a new mode of watching movies in recent years. As a breakthrough in the development of the post-movie industry, the on-demand cinemas rely on private booths, high-quality hardware and rich movie resources to provide audiences with new and fresh watching experiences. The recommendation system for on-demand cinemas is to recommend to cinemas movies that may be of interest to their potential audiences, and provide an individualized recommendation service for preparing movie storage of on-demand cinemas to meet the audiences’ preferences and instant watching needs. The characteristics implied in the audience behaviors of on-demand cinemas make the recommendation method for them different from those for online videos, items in offline stores or a group of users. In this paper, we describe the challenges and build a system for this application scenario, which fuses the historical on-demand records of cinemas, the POI (Point of Interest) information around cinemas and the content descriptions of movies, and explores the temporal dynamics and spatial influences rooted in audience behaviors. A WeChat applet customized for on-demand cinema staffs/hosts, as the client of our system, has been put into in practice.