@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, 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 = "Howard Ho and Ooi, \{Beng Chin\} and Zaki, \{Mohammed J.\} and Xiaohua Hu and Laura Haas and Vipin Kumar and Sudarsan Rachuri and Shipeng Yu and Hsiao, \{Morris Hui-I\} and Jian Li and Feng Luo and Saumyadipta Pyne and Kemafor Ogan",
booktitle = "Proceedings - 2015 IEEE International Conference on Big Data, Big Data 2015",
}