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 ...

In multivariate time series analysis, pre-processing is integral for enabling analysis, but inevitably introduces uncertainty into the data. Enabling the assessment of the uncertainty and allowing uncertainty-aware analysis, ...

We present the Contingency Wheel, a visual method for finding and analyzing associations in a large nxm contingency table with m less than 100 and n being two to three orders of magnitude larger than m. The method is ...

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 ...

Time series appear in many different domains. The main goal in time series analysis is to find a model for given time series. The selection of time series models is done iteratively based, usually, on information criteria ...

Multivariate networks are complex data structures, which are ubiquitous in many application domains. Driven by a real-world problem, namely the movement behavior of citizens in Vienna, we designed and implemented a Visual ...

For the automatic segmentation of multivariate time series domain experts at first need to consider a huge space of alternative configurations of algorithms and parameters. We assume that only a small subset of these ...

Exploratory data analysis of time-oriented data is an important goal that Visual Analytics has to tackle. When users from real-world domains are asked about time-oriented tasks, they often refer to the unique structure of ...