Security and quality are main concerns for private and public financial institutions. Data mining techniques based on the profiles of customers of a financial institution are commonly used to avoid fraud and financial ...

Despite the growing interest for visualization of sentiments and emotions in textual data, the task of detecting and visualizing various stances is not addressed well by the existing approaches. The challenges associated ...

Curriculum Vitae (CV) is an established representation of a person's academic and professional history. A typical CV is comprised of multiple sections associated with spatial, temporal, nominal, and ordinal data. Commonly, ...

The segmenting and labeling of multivariate time series data is applied in different domains, e.g. activity recognition or sensor states. This involves several steps of (pre-) processing, segmenting, and labeling of time ...

While open data platforms are increasingly popular among end-users as well as data providers, there is a growing problem with inconsistent update frequencies and lack of quality in datasets. Efforts to monitor data quality ...

Digitalization increases the opportunity to collect vast amounts of data in a large scale manner. In order to handle the information overload, data mining techniques like online clustering are performed. A lot of online ...

Train trip planning means deciding on one of several travel connections. Possible train delays lead to uncertainties in the schedule connections and may influence the planning decisions. Although several designs for the ...

Parameter analysis can be used to find out how individual parameters influence the output of an algorithm. We aim to support the visual parameter analysis of algorithms for the segmentation of time series. To this end, we ...

Finding the most accurate image segmentation involves analyzing results from different algorithms or parameterizations. In this work, we identify different types of uncertainty in this analysis that are represented by the ...