Exploiting ratings and trust to resolve the data sparsity and cold start of recommender systems

• 主要作者: Guo, Guibing
• 其他作者: Jie Zhang
• 格式: Theses and Dissertations
• 語言: English
• 出版: 2015
• 主題: DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications
• 在線閱讀: https://hdl.handle.net/10356/64555
• 機構: Nanyang Technological University

Collaborative filtering (CF) is a widely used technique for recommender systems. The essential principle is that users with similar preference in the past are likely to give similar ratings on the items of interest in the future. However, collaborative filtering inherently suffers from two severe issu...