@inproceedings{1b542a1f543e41e39132945b01dacc2a,
title = "Profit estimation error analysis in recommender systems based on association rules",
abstract = "It is a challenge to estimate expected benefits from recommender systems based on association rule mining. This paper aims to address this challenge and presents a study of buying preferences of a sample of retail customers. It reveals a monotonic, non-linear relationship between the expected profits (as a function of information loss) and minimum support threshold levels, when considering transactions for a recommender system based on association rules. This finding is significant for recommender systems that utilize potential profits as a decision-making criterion.",
keywords = "association mining, association rules, profit estimation, recommender systems, retail industry",
author = "Gurdal Ertek and Xu Chi and Gabriel Yee and Yong, {Ong Boon} and Choi, {Byung Geun}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Big Data, IEEE Big Data 2015 ; Conference date: 29-10-2015 Through 01-11-2015",
year = "2015",
month = dec,
day = "22",
doi = "10.1109/BigData.2015.7363998",
language = "English",
series = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2138--2142",
editor = "Feng Luo and Kemafor Ogan and Zaki, {Mohammed J.} and Laura Haas and Ooi, {Beng Chin} and Vipin Kumar and Sudarsan Rachuri and Saumyadipta Pyne and Howard Ho and Xiaohua Hu and Shipeng Yu and Hsiao, {Morris Hui-I} and Jian Li",
booktitle = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
}