# Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics

arXiv: https://arxiv.org/abs/1501.07716 · HTML: https://mlsanity.com/paper/1501.07716/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2015.

## Built on by (most cited first, 2 of 2)

- [Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems](https://mlsanity.com/paper/2203.00376/) (2022)
- [A conceptual model for leaving the data-centric approach in machine learning](https://mlsanity.com/paper/2302.03361/) (2023)

## Abstract (arXiv)

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.