Embedding-Enhanced Similarity Metrics for Next POI Recommendation

Sara Jarrad, Hubert Naacke, Stephane Gancarski, Modou Gueye

2023

Abstract

Social media platforms allow users to share information, including photos and tags, and connect with their peers. This data can be used for innovative research, such as proposing personalized travel destination recommendations based on user-generated traces. This study aims to demonstrate the value of using embeddings, which are dense real-valued vectors representing each visited location, in generating recommendations for the next Point of Interest (POI) to visit based on the last POI visited. The Word2Vec language model is used to generate these embeddings by considering POIs as words and sequences of POIs as sentences. This model captures contextual information and identifies similar contexts based on the proximity of numerical vectors. Empirical experiments conducted on a real dataset show that embedding-based methods outperform conventional methods in predicting the next POI to visit.

Paper Citation

in Harvard Style

Jarrad S., Naacke H., Gancarski S. and Gueye M. (2023). Embedding-Enhanced Similarity Metrics for Next POI Recommendation. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 247-254. DOI: 10.5220/0012060300003541

in Bibtex Style

@conference{data23,
author={Sara Jarrad and Hubert Naacke and Stephane Gancarski and Modou Gueye},
title={Embedding-Enhanced Similarity Metrics for Next POI Recommendation},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={247-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012060300003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Embedding-Enhanced Similarity Metrics for Next POI Recommendation
SN - 978-989-758-664-4
AU - Jarrad S.
AU - Naacke H.
AU - Gancarski S.
AU - Gueye M.
PY - 2023
SP - 247
EP - 254
DO - 10.5220/0012060300003541
PB - SciTePress