Augmented Semantic Explanations for Collaborative Filtering Recommendations

Mohammed Alshammari, Olfa Nasraoui

2019

Abstract

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the rating for unseen items with high accuracy. However, they fail to justify their output. The main objective of this paper is to present a novel approach that employs Semantic Web technologies to generate explanations for the output of black box recommender systems. The proposed model significantly outperforms state-of-the-art baseline models in terms of the error rate. Moreover, it produces more explainable items than all baseline approaches.

Paper Citation

in Harvard Style

Alshammari M. and Nasraoui O. (2019). Augmented Semantic Explanations for Collaborative Filtering Recommendations. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 83-88. DOI: 10.5220/0008070900830088

in Bibtex Style

@conference{kdir19,
author={Mohammed Alshammari and Olfa Nasraoui},
title={Augmented Semantic Explanations for Collaborative Filtering Recommendations},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={83-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008070900830088},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - Augmented Semantic Explanations for Collaborative Filtering Recommendations
SN - 978-989-758-382-7
AU - Alshammari M.
AU - Nasraoui O.
PY - 2019
SP - 83
EP - 88
DO - 10.5220/0008070900830088
PB - SciTePress