Adaptive Serendipity for Recommender Systems: Let It Find You

Miriam Badran, Jacques Abdo, Wissam Jurdi, Jacques Demerjian

Abstract

Recommender systems are nowadays widely implemented in order to predict the potential objects of interest for the user. With the wide world of the internet, these systems are necessary to limit the problem of information overload and make the user’s internet surfing a more agreeable experience. However, a very accurate recommender system creates a problem of over-personalization where there is no place for adventure and unexpected discoveries: the user will be trapped in filter bubbles and echo rooms. Serendipity is a beneficial discovery that happens by accident. Used alone, serendipity can be easily confused with randomness; this takes us back to the original problem of information overload. Hypothetically, combining accurate and serendipitous recommendations will result in a higher user satisfaction. The aim of this paper is to prove the following concept: including some serendipity at the cost of profile accuracy will result in a higher user satisfaction and is, therefore, more favourable to implement. We will be testing a first measure implementation of serendipity on an offline dataset that lacks serendipity implementation. By varying the ratio of accuracy and serendipity in the recommendation list, we will reach the optimal number of serendipitous recommendations to be included in an accurate list.

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Paper Citation


in Harvard Style

Badran M., Abdo J., Jurdi W. and Demerjian J. (2019). Adaptive Serendipity for Recommender Systems: Let It Find You.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 739-745. DOI: 10.5220/0007409507390745


in Bibtex Style

@conference{icaart19,
author={Miriam Badran and Jacques Abdo and Wissam Jurdi and Jacques Demerjian},
title={Adaptive Serendipity for Recommender Systems: Let It Find You},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={739-745},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007409507390745},
isbn={978-989-758-350-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Adaptive Serendipity for Recommender Systems: Let It Find You
SN - 978-989-758-350-6
AU - Badran M.
AU - Abdo J.
AU - Jurdi W.
AU - Demerjian J.
PY - 2019
SP - 739
EP - 745
DO - 10.5220/0007409507390745