The recent advances in natural language based interaction methodologies offer promising avenues to enhance the interactive processes within the human-machine dialogue of visual analytics. We envisage Multimodal Data Analytics ...

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 ...

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 ...

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 ...

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 ...

Sparklines are placed in documents but their usability is rarely evaluated in their immediate context of paragraphs of text. We conducted an eye-tracking study to measure readability and understandability of four different ...

Information retrieval provides to date effective methods to search for documents relevant to user queries, and to support exploration of clusters of similar documents. Typically, the retrieval relies on text-based queries ...

We present novel direct-touch centered paradigms for exploring time series data visualized in a coordinated multi-view display. The views can be easily and flexibly configured by choosing from various adapted or enhanced ...