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Authors: Silvia Rossi ; Francesco Cervone and Francesco Barile

Affiliation: Università degli Studi di Napoli Federico II, Italy

ISBN: 978-989-758-219-6

Keyword(s): Group Recommendations, Weighted Utilities, Off-line Testing.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Group Decision Making

Abstract: One of the major issue in designing group recommendation techniques relates to the difficulty of the evaluation process. Up-today, no freely available dataset exists that contains information about groups, like, for example, the group’s choices or social aspects that may characterize the group’s members. The objective of the paper is to analyze the possibility to make an evaluation of ranking-based groups recommendation techniques by using offline testing. Typically, the evaluation of group recommendations is computed, as in the classical single user case, by comparing the predicted group’s ratings with respect to the single users’ ratings. Since the information contained in the datasets are mainly such user’s ratings, here, ratings are used to define different ranking metrics. Results suggest that such an attempt is hardly feasible. Performance seems not to be affected by the choice of ranking technique, except for some particular cases. This could be due to the averaging effect of t he evaluation with respect to the single users’ ratings, so a deeper analysis or specific dataset are necessary. (More)

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Paper citation in several formats:
Rossi, S.; Cervone, F. and Barile, F. (2017). An Off-line Evaluation of Users’ Ranking Metrics in Group Recommendation.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 252-259. DOI: 10.5220/0006200702520259

@conference{icaart17,
author={Silvia Rossi. and Francesco Cervone. and Francesco Barile.},
title={An Off-line Evaluation of Users’ Ranking Metrics in Group Recommendation},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={252-259},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006200702520259},
isbn={978-989-758-219-6},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - An Off-line Evaluation of Users’ Ranking Metrics in Group Recommendation
SN - 978-989-758-219-6
AU - Rossi, S.
AU - Cervone, F.
AU - Barile, F.
PY - 2017
SP - 252
EP - 259
DO - 10.5220/0006200702520259

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