This paper explores possibilities for marrying data visualization to online archival finding aids, which have continually suffered from usability issues in their long history. This paper describes a project in which two different data visualization models were built to replace sections of an archival finding aid. Users were then shown the models,…

In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association rules. This research fills this gap by describing a method based on discrete wavelet transform (DWT) to protect input data privacy while preserving…