@inbook{55dbee01ede44bf0bc77355f4b581f4b,
title = "A new scheme on privacy preserving association rule mining",
abstract = "We address the privacy preserving association rule mining problem in a system with one data miner and multiple data providers, each holds one transaction. The literature has tacitly assumed that randomization is the only effective approach to preserve privacy in such circumstances. We challenge this assumption by introducing an algebraic techniques based scheme. Compared to previous approaches, our new scheme can identify association rules more accurately but disclose less private information. Furthermore, our new scheme can be readily integrated as a middleware with existing systems.",
author = "Nan Zhang and Shengquan Wang and Wei Zhao",
year = "2004",
doi = "10.1007/978-3-540-30116-5_44",
language = "English (US)",
isbn = "3540231080",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "484--495",
editor = "Jean-Francois Boulicaut and Floriana Esposito and Fosca Giannotti and Dino Pedreschi",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}