# Local Collaborative Filtering: A Collaborative Filtering Method that Utilizes Local Similarities among Users

arXiv: https://arxiv.org/abs/2511.13166 · HTML: https://mlsanity.com/paper/2511.13166/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 17 Nov 2025.

## Builds on (most cited first, 1 of 1)

- [Modeling User Exposure in Recommendation](https://mlsanity.com/paper/1510.07025/) (2015)

## Abstract (arXiv)

To leverage user behavior data from the Internet more effectively in recommender systems, this paper proposes a novel collaborative filtering (CF) method called Local Collaborative Filtering (LCF). LCF utilizes local similarities among users and integrates their data using the law of large numbers (LLN), thereby improving the utilization of user behavior data. Experiments are conducted on the Steam game dataset, and the results of LCF align with real-world needs.