Experimental comparison of recommender systems

• Main Author: See, Jie Xun
• Other Authors: Xavier Bresson
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
• Online Access: http://hdl.handle.net/10356/76935
• Institution: Nanyang Technological University

Recommender systems seek to predict the rating that a user would give an item, given the data of the past ratings of all users and items and other side information. Traditionally, recommender system methods are split into two broad categories: content-based and collaborative filtering approaches. Ho...