Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics
This addresses a limitation in resource recommendation systems for users, though it appears incremental as it refines an existing method.
The paper tackles the problem of classic resource recommenders neglecting non-linear user-resource dynamics by proposing a novel hybrid recommendation strategy that refines Collaborative Filtering. The approach substantially improves CF and successfully competes with a more expensive Matrix Factorization variant on some datasets.
Classic resource recommenders like Collaborative Filtering (CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and interpretation. In this paper, we propose a novel hybrid recommendation strategy that refines CF by capturing these dynamics. The evaluation results reveal that our approach substantially improves CF and, depending on the dataset, successfully competes with a computationally much more expensive Matrix Factorization variant.