The goal of process discovery is to visualize event log data as a process model. In reality,
however, these models are often highly complex. Process trace clustering is a well-studied …

Today's applications generate a large amount of data that need to be processed by learning
algorithms. In practice, the majority of the data are not associated with any labels …

Short text clustering is a challenging task due to the lack of signal contained in short texts. In
this work, we propose iterative classification as a method to boost the clustering quality of …

For centuries quality of life was a subject of studies across different disciplines. However,
only with the emergence of a digital era, it became possible to investigate this topic on a …

This thesis focuses on the efficient clustering of short texts along with an application to find
duplicate questions in Stack Overflow. In the first part of this thesis, we discuss static and …

The utilization of process mining event logs has emerged as a pivotal strategy for
organizations to achieve business intelligence, comprehend their processes, pinpoint …

Background Chronic kidney disease (CKD) is a common, complex, and heterogeneous
disease impacting aging populations. Determining the landscape of disease progression …

Cluster analysis is the process of partitioning a set of data objects into subsets, each subset
is a cluster, so that objects within a cluster have high similarity, but are very dissimilar to …

This paper presents a novel approach to lessen the hubness dilemma and identify the curse
of dimensionality present in the high dimensional data by means of the shared nearest …

Accurate forecast of cyclone intensities is important for disaster preparedness in the coastal
areas. Intensity prediction becomes especially difficult when they undergo rapid …