A Serendipity-Oriented Greedy Algorithm for Recommendations

Denis Kotkov, Jari Veijalainen, Shuaiqiang Wang

2017

Abstract

Most recommender systems suggest items to a user that are popular among all users and similar to items the user usually consumes. As a result, a user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected, i.e. serendipitous items. In this paper, we propose a serendipity-oriented algorithm, which improves serendipity through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm and compare it with others, we employ a serendipity metric that captures each component of serendipity, unlike the most common metric.

Paper Citation

in Harvard Style

Kotkov D., Veijalainen J. and Wang S. (2017). A Serendipity-Oriented Greedy Algorithm for Recommendations . In Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-246-2, pages 32-40. DOI: 10.5220/0006232800320040

in Bibtex Style

@conference{webist17,
author={Denis Kotkov and Jari Veijalainen and Shuaiqiang Wang},
title={A Serendipity-Oriented Greedy Algorithm for Recommendations},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2017},
pages={32-40},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006232800320040},
isbn={978-989-758-246-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - A Serendipity-Oriented Greedy Algorithm for Recommendations
SN - 978-989-758-246-2
AU - Kotkov D.
AU - Veijalainen J.
AU - Wang S.
PY - 2017
SP - 32
EP - 40
DO - 10.5220/0006232800320040