Assigning reliability values to recommendations using matrix factorization

作者：Zhu, B.; Ortega, F.; Bobadilla, J.^*; Gutierrez, A.

来源：Journal of Computational Science, 2018, 26: 165-177.

DOI：10.1016/j.jocs.2018.04.009

• Reliability
• Confidence
• Collaborative filtering
• Matrix factorization

Providing a reliability value to each prediction and recommendation is very important in current recommender systems: Users should know which recommendations are reliable and which ones are risky. Despite its growing importance, research into collaborative filtering reliability has rarely been developed in the model-based area. This paper explains a matrix factorization-based architecture and method that provides a reliability value to each prediction/recommendation. The reliability values obtained have been put to the test, and, when applied, they show improvements in prediction and recommendation quality in different recommender systems; additionally, they provide a range of values that are understandable to users.

• 出版日期2018-5
• 单位北京理工大学