Spatial-Temporal Recommendation for On-demand Cinemas

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.

This work was supported by the National Natural Science Foundation of China (No. 61472408) and the joint project with iQIYI (No. LUM18-200032).