There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources — sensor data, experimental data, data from ...
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...
Association rule mining is an important data mining problem. It is found to be useful for conventional relational data. However, previous work has mostly targeted on mining a sing...
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the dat...
This paper describes an approach to temporal pattern mining
using the concept of user dened temporal prototypes to dene the
nature of the trends of interests. The temporal patt...
Vassiliki Somaraki, Deborah Broadbent, Frans Coene...