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Authors: Aroua Essayeh and Mourad Abed

Affiliation: LAMIH, France

Keyword(s): Clustering, Learning Machine, Ontology, Public Transportation.

Related Ontology Subjects/Areas/Topics: Applications of Expert Systems ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Data Engineering ; Enterprise Information Systems ; Group Decision Support Systems ; Information Systems Analysis and Specification ; Intelligent Transportation System ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Symbolic Systems

Abstract: In traditional transport information systems, the users must explicitly provide the information related to both their profiles and travels to receive a personalized response. However, this requires, among others, an extra effort from user in term of search time. We aim to identify not only implicitly users’ information, but also to anticipate their need even if some data are missing through a recommender system based on collaborative filtering technique. In this work, the information related to users is represented using the ontology which proved far more adequate model for representing semantically data.

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Paper citation in several formats:
Essayeh, A. and Abed, M. (2017). A Recommendation System for Enhancing the Personalized Search Itineraries in the Public Transportation Domain. In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-247-9; ISSN 2184-4992, SciTePress, pages 415-423. DOI: 10.5220/0006315904150423

@conference{iceis17,
author={Aroua Essayeh. and Mourad Abed.},
title={A Recommendation System for Enhancing the Personalized Search Itineraries in the Public Transportation Domain},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2017},
pages={415-423},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006315904150423},
isbn={978-989-758-247-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - A Recommendation System for Enhancing the Personalized Search Itineraries in the Public Transportation Domain
SN - 978-989-758-247-9
IS - 2184-4992
AU - Essayeh, A.
AU - Abed, M.
PY - 2017
SP - 415
EP - 423
DO - 10.5220/0006315904150423
PB - SciTePress