Leveraging Large Language Models for Recommendation and Explanation

Abstract

We demonstrate a proof of concept web application that recommends movies and generates explanations for the recommendations using Large Language Models (LLMs). Specifically, the application uses ChatGPT as both a movie recommender and model for generating explanations of the recommendations. The application gathers user preferences (liked movies), user goals (type of recommendations), and offers personalized recommendations and explanations tailored according to the used-defined goals. In this demo, we showcase how recommendations and explanations can be customized according to user-defined criteria, such as personalization, novelty, or popularity, and implemented using LLMs.