Movie Recommender System with Perceptual Engineering in Chatbot

Abstract

 This study proposed Movie Recommender System (MRS) with a Perceptual Engineering (PE) in Chatbot. We call this system as MRS-PE that could reflect users preferences and achieve their expected looking movie results. To display effect of our MRS-PE system, we insert the system into LINE that is a social Chatbot system. To complete these building processes, we divided the system into four parts: (1) Web Crawler; (2) Decision of Perceptions; (3) Building MRS with PE and (4) Building Chatbot. The Yahoo Movie website was selected as a database for demonstrating our MRS-PE system in Chatbot. The users can check out movie Chatbot to view the proposed movie results based on users preferences before going to the movie theater. After receiving a recommended movie, users can also determine which movie theater to go and purchase online tickets first. The results show that people would like to use our movie Chatbot before going to movie theater because save their purchase time and reduces searching movie time.