Classification rules are an important tool for discovering knowledge from databases. Integrating fuzzy logic algorithms into databases allows us to reduce uncertainty which is connected with data in databases and to increase discovered knowledge’s accuracy. In this paper, we analyze some possible variants of making classification rules from a given fuzzy decision based on cumulative information...

The explosive growth of string databases makes similarity search a challenging problem. Current search tools are non-interactive in the sense that the user has to wait a long time until the entire database is inspected. We consider the problem of interactive searching, and propose a set of innovative -NN ( -Nearest Neighbor) search algorithms. We propose a new model for the distance distributio...

In the context of statistical databases, the release of accurate statistical information about the collected data often puts at risk the privacy of the individual contributors. The goal of differential privacy is to maximise the utility of a query while protecting the individual records in the database. A natural way to achieve differential privacy is to add statistical noise to the result of t...

Predictive data mining is concerned with constructing statistical models from historical data. These models are used to predict future unknown data values, and/or to help gain an understanding of the predictive relationships represented in the data. The data consists of sets of measurements made on objects (observations) collected in a data base. One of the measured variables (denoted by y) is ...

Differential privacy is a recent notion of privacy for statistical databases that provides rigorous, meaningful confidentiality guarantees, even in the presence of an attacker with access to arbitrary side information. We show that for a large class of parametric probability models, one can construct a differentially private estimator whose distribution converges to that of the maximum likeliho...

Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear corre...

Background As a registered clinical trials unit we develop customised databases to collect and store study data and manage clinical trials; these databases need rigorous testing to ensure they function as intended, that data validation is implemented correctly and that study data extracts are complete and accurate. We describe how, with statistical involvement, the testing has been streamlined ...