We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on...
We identify proximity breach as a privacy threat specific to numerical sensitive attributes in anonymized data publication. Such breach occurs when an adversary concludes with hig...
We contribute to the research on stable minimum storage merging by introducing an algorithm that is particularly simply structured compared to its competitors. The presented algori...
One of the major puzzles in performing multi-agent-based simulations is the validity of their results. Optimisation of simulation parameters can lead to results that can be deceit...
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...