The main contributions of this approach can be classified into separate
In this work, we use three real-world well-known check-in datasets Gowalla, Foursquare, and Yelp datasets
We have evaluated datasets with different sample rates used in the offline experiments
We have analyzed the impact of Unfairness of Popularity Bias in Point-of-Interest Recommendation.
The proposed approach was robust in terms of providing valuable outcomes.
The full evaluation results are presented in tables below:
We are a diverse group of individuals who bring perspectives to the state-of-the-art projects.
You can cite our paper using the reference text below:
@article{rahmani2022unfairness,
author = {Hossein A. Rahmani and Yashar Deldjoo and Ali Tourani and Mohammadmehdi Naghiaei},
title = {The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation},
year = {2022},
url = {https://arxiv.org/abs/2202.13307},
archivePrefix = {arXiv},
primaryClass = {cs.IR},
eprint = {2202.13307}
}
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