Tourism Integrated Recommender System: Setubal Peninsula Case Study

Mohamma Julashokri; Suzana Monteiro Leonardi; Pedro Seabra

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Paper

Tourism Integrated Recommender System: Setubal Peninsula Case Study

Topics: Group Decision Support Systems; Tools, Techniques and Methodologies for System Development

In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS, 623-627, 2022

Authors: Mohamma Julashokri ¹ ; Suzana Monteiro Leonardi ² and Pedro Seabra ¹

Affiliations: ¹ Viatecla SA, Estr. Algazarra 72, 2810-013 Almada, Portugal ; ² Faculdade de Letras, Universidade de Lisboa, Lisboa, Portugal

Keyword(s): Tourism, Recommender System, Collaborative Filtering, Content-based Filtering, Point of Interest.

Abstract: The diversity and a huge number of different places and attractions can make the decision for tourists difficult. The recommender systems are developed to facilitate people's decision-making process that can help in the area of tourism as well. In this paper, we proposed and implement a recommender system that works integrated with a Setubal peninsula portal to help tourists to choose experiences and points of interest to visit. The implementation was done using collaborative and content-based filtering to make recommendations based on user profiles and activities within the portal.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Julashokri, M., Leonardi, S. M. and Seabra, P. (2022). Tourism Integrated Recommender System: Setubal Peninsula Case Study. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 623-627. DOI: 10.5220/0011102100003179

@conference{iceis22,
author={Mohamma Julashokri and Suzana Monteiro Leonardi and Pedro Seabra},
title={Tourism Integrated Recommender System: Setubal Peninsula Case Study},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2022},
pages={623-627},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011102100003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Tourism Integrated Recommender System: Setubal Peninsula Case Study
SN - 978-989-758-569-2
IS - 2184-4992
AU - Julashokri, M.
AU - Leonardi, S.
AU - Seabra, P.
PY - 2022
SP - 623
EP - 627
DO - 10.5220/0011102100003179
PB - SciTePress