Mykola Pechenizkiy

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Concept drift primarily refers to an online supervised learning scenario when the relation between the input data and the target variable changes over time. Assuming a general knowledge of supervised learning in this article, we characterize adaptive learning processes; categorize existing strategies for handling concept drift; overview the most(More)
Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact that often available historic data is biased due to(More)
A hypermedia application offers its users much freedom to navigate through a large hyperspace. Adaptive Hypermedia (AH) offers personalized content, presentation and navigation support. Many Adaptive Hypermedia Systems (AHS) are tightly integrated with one specific application and/or use a limited number of techniques and methods. This makes it difficult to(More)
In the real world concepts are often not stable but change with time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as new pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift, complicates the task of learning a(More)
Although most business processes change over time, contemporary process mining techniques tend to analyze these processes as if they are in a steady state. Processes may change suddenly or gradually. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). For the process management, it is(More)
Operational processes need to change to adapt to changing circumstances, e.g., new legislation, extreme variations in supply and demand, seasonal effects, etc. While the topic of flexibility is well-researched in the BPM domain, contemporary process mining approaches assume the process to be in steady state. When discovering a process model from event logs,(More)
Diversity inside a group of users having their individual abilities, interests, and needs challenge the developers of eHealth projects with heterogeneous needs in information delivery and/or other eHealth services. This paper considers an adaptive user interface approach as an opportunity in addressing this challenge. We briefly overview the recent(More)