Recommending Points of Interest with a Context-Aware Dual Recurrent Neural Network

Lucas Silva Couto, Gislaine Leal, Marcos Aurélio Domingues

2025

Abstract

The advent of location-based social networks (LBSNs) has reshaped how users engage with their surroundings, facilitating personalized connections with nearby points of interest (POIs) like restaurants, tourist attractions, and so on. To help the users to find points that fit their interests, recommender systems can be used to filter a large number of POIs according to the users’ preferences. However, the context in which the users make their check-ins must be taken into account, which justifies the usage of context-aware recommender systems. The goal of this work is to use a Context-Aware Dual Recurrent Neural Network to acquire contextual information (represented by embeddings) for each POI, given the sequence of points that each user has checked-in. Then, the contextual information (i.e. the embeddings) is used by context-aware recommenders to suggest POIs. We evaluated the contextual information by using four context-aware recommender systems in two datasets. The results showed that the contextual information obtained by our proposed method presents better results than the state-of-the-art method proposed in the literature.

Paper Citation

in Harvard Style

Couto L., Leal G. and Domingues M. (2025). Recommending Points of Interest with a Context-Aware Dual Recurrent Neural Network. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 1061-1068. DOI: 10.5220/0013230000003929

in Bibtex Style

@conference{iceis25,
author={Lucas Couto and Gislaine Leal and Marcos Domingues},
title={Recommending Points of Interest with a Context-Aware Dual Recurrent Neural Network},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={1061-1068},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013230000003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Recommending Points of Interest with a Context-Aware Dual Recurrent Neural Network
SN - 978-989-758-749-8
AU - Couto L.
AU - Leal G.
AU - Domingues M.
PY - 2025
SP - 1061
EP - 1068
DO - 10.5220/0013230000003929
PB - SciTePress