Placement-and-Profit-Aware Association Rules Mining
Runyu Ma, Hantian Li, Jin Cen, Amrinder Arora
2019
Abstract
Previous approaches on association rule mining in recommendation have already achieved promising performances. However, to the best of our knowledge, they seldom simultaneously take the profit and placement factor into consideration. In E-commerce recommendation scenario, the order of the recommendation reflects as placement. In this paper, we propose a novel placement-and-profit-aware association rule mining algorithm to maximize profit as well as maintaining recommendation accuracy. We also propose two metrics: Expectation of Profit (EOP), which measures the overall profit, and Expectation of Click rate (EOC), which measures the user experience. Experiments on SPMF dataset show that the proposed algorithm can improve the EOP significantly with only slight decrease in EOC.
DownloadPaper Citation
in Harvard Style
Ma R., Li H., Cen J. and Arora A. (2019). Placement-and-Profit-Aware Association Rules Mining.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 639-646. DOI: 10.5220/0007380606390646
in Bibtex Style
@conference{icaart19,
author={Runyu Ma and Hantian Li and Jin Cen and Amrinder Arora},
title={Placement-and-Profit-Aware Association Rules Mining},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={639-646},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007380606390646},
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 - Placement-and-Profit-Aware Association Rules Mining
SN - 978-989-758-350-6
AU - Ma R.
AU - Li H.
AU - Cen J.
AU - Arora A.
PY - 2019
SP - 639
EP - 646
DO - 10.5220/0007380606390646