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Network Analysis for Financial Fraud Detection
(The Eurographics Association, 2018)
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 ...
CV3: Visual Exploration, Assessment, and Comparison of CVs
(The Eurographics Association, 2018)
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, ...
Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data
(The Eurographics Association, 2018)
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 ...
Visually Exploring Data Provenance and Quality of Open Data
(The Eurographics Association, 2018)
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 ...
Visual Analytics for Fraud Detection: Focusing on Profile Analysis
(The Eurographics Association, 2016)
Financial institutions are always interested in ensuring security and quality for their customers. Banks, for instance, need to identify and avoid harmful transactions. In order to detect fraudulent operations, data mining ...
Shapes of Time: Visualizing Set Changes Over Time in Cultural Heritage Collections
(The Eurographics Association, 2019)
In cultural heritage collections, categorization is a central technique used to distinguish cultural movements, styles, or genres. For that end, objects are tagged with set-typed metadata and other information, such as ...