Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2011

This study focused on the idea of applying a trust metric and a recommendation engine for a recommendation system. The study resulted in developing a trust metric and a recommendation algorithm that is based on a user's trust network. The system's aim is to propose a trust metric function capable of predicting trust values for a user to be given an idea on how much another user is trustworthy, a recommendation engine that recommends movies to users that are both acceptable and appealing, and being able to integrate and test both by integrating both t a movie information system. The trust metric bases its prediction on the rating behavior of users towards movies in the online Movie Recommender System (oMRS), the movie information system being used, and that certain user's reputation. Having users to rate movies in the oMRS, the most rated genre will be the context used for personalized movie recommendations, and either the global or local trust network, depending n how many other users a certain user trusts, will further provide more personalized movie recommendations. The trust metric and the recommendation engine were implemented using HTML and PHP, integrated to the oMRS, also implemented using HTML and PHP, and both uses MySQL for database usage.