Movie Recommendation Using Conversational Mechanism and Knowledge Based Filtering

Abstract

Conversational recommender system created for helping users in searching information in a domain by using conversational mechanism. These systems help user to get recommendation by selecting items that most suitable to user’s preference by asking user needed. The recommendations generated by eliciting user’s experience e.g. his favourite movies, actor and director and then gives the item that match their interest. There are many methods to get the suitable recommendation that match the user’s preference. In this paper, we use ontology which represents knowledge to get result of recommendation that fit to user preference by using knowledge-based filtering to determine the user’s need. Our system has been implemented for movie domain. We test our system performance by studying user's perception.