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Data Mining: the search for knowledge in databases M. Holsheimer, APJM Siebes Computer …

Association rules are amongst the most important patterns that can be discovered using data
mining. Their automatic discovery is supported by most, if not all, data mining software tools…

We present a method of detecting and localising outliers in financial time series and other
stochastic processes. The method checks the internal consistency of the scaling behaviour of …

There has been an increase in the use of machine learning and artificial intelligence (AI) for
the analysis of image-based cellular screens. The accuracy of these analyses, however, is …

We present a method of detecting and localising outliers in stochastic processes. The
method checks the internal consistency of the scaling behaviour of the process within the …

High-throughput techniques, such as DNA microarrays, that are used in gene expression
measurements offer a unique and global insight into the molecular mechanisms of a living cell. …

Advances in the area of active database management systems require the development of a
trigger design theory, which guides the user in the definition off well-behaving trigger based …

Technology-Assisted Review (TAR) aims to reduce the human effort required for screening
processes such as abstract screening for systematic literature reviews. Human reviewers …

Data mining aims at extracting hidden knowledge from the information stored in a data
warehouse to identify the preferences of customers, derive decision models for business …

One of the major problems in frequent pattern mining is the explosion of the number of
results, making it difficult to identify the interesting frequent patterns. In a recent paper [14] we …