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Authors: Jaime Wojciechowski ; Rafael Romualdo Wandresen ; Rafaela Mantovani Fontana ; João Eugênio Marynowski and Alexander Robert Kutzke

Affiliation: Federal University of Paraná, Brazil

Keyword(s): Recommendation Systems, E-commerces, Collaborative Filtering, Content-based Filtering.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: Recommendation systems may use different algorithms to present relevant information to users. In e-commerce contexts, these systems are essential to provide users with a customized experience. Several studies have evaluated different recommendation algorithms against their accuracy, but only a few evaluate algorithms from the user satisfaction viewpoint. We here present a study that aims to identify how different recommendation algorithms trigger different perceptions of satisfaction on users. Our research approach was an experiment using products and sales data from a real small retailer. Users expressed their satisfaction perception for three different algorithms. The study results show that the algorithms proposed did not trigger different perceptions of satisfaction on users, giving clues of improvements to small retailers websites.

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Paper citation in several formats:
Wojciechowski, J.; Wandresen, R.; Mantovani Fontana, R.; Marynowski, J. and Robert Kutzke, A. (2017). Is Products Recommendation Good? An Experiment on User Satisfaction. In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-248-6; ISSN 2184-4992, SciTePress, pages 713-720. DOI: 10.5220/0006316307130720

@conference{iceis17,
author={Jaime Wojciechowski. and Rafael Romualdo Wandresen. and Rafaela {Mantovani Fontana}. and João Eugênio Marynowski. and Alexander {Robert Kutzke}.},
title={Is Products Recommendation Good? An Experiment on User Satisfaction},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2017},
pages={713-720},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006316307130720},
isbn={978-989-758-248-6},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Is Products Recommendation Good? An Experiment on User Satisfaction
SN - 978-989-758-248-6
IS - 2184-4992
AU - Wojciechowski, J.
AU - Wandresen, R.
AU - Mantovani Fontana, R.
AU - Marynowski, J.
AU - Robert Kutzke, A.
PY - 2017
SP - 713
EP - 720
DO - 10.5220/0006316307130720
PB - SciTePress