scispace - formally typeset
M

Michael Granitzer

Researcher at University of Passau

Publications -  237
Citations -  3253

Michael Granitzer is an academic researcher from University of Passau. The author has contributed to research in topics: Computer science & Semantic Web. The author has an hindex of 26, co-authored 216 publications receiving 2927 citations. Previous affiliations of Michael Granitzer include Graz University of Technology & University of Graz.

Papers
More filters
Journal ArticleDOI

Sequence Classification for Credit-Card Fraud Detection

TL;DR: It is shown that the LSTM improves detection accuracy on offline transactions where the card-holder is physically present at a merchant, and both the sequential and non-sequential learning approaches benefit strongly from manual feature aggregation strategies.
Proceedings ArticleDOI

On the Beauty and Usability of Tag Clouds

TL;DR: A family of novel algorithms for tag cloud layout is proposed and evaluation results obtained from an extensive user study and a technical evaluation enable designers to devise a combination of algorithm and parameters which produces satisfying tag cloud layouts for many application scenarios.
Journal ArticleDOI

The InfoSky visual explorer: exploiting hierarchical structure and document similarities

TL;DR: InfoSky is a system enabling users to explore large, hierarchically structured document collections using a planar graphical representation with variable magnification, and can map metadata such as document size or age to attributes of the visualisation such as colour and luminance.
Journal IssueDOI

Combining BPM and social software: contradiction or chance?

TL;DR: The results of the workshop on Business Process Management and Social Software (BPMS2'08), as part of the International Conference on Business process Management in Milano, show the manifold possibilities of combining concepts from Business Process management and social software.
Proceedings ArticleDOI

Accelerating K-Means on the Graphics Processor via CUDA

TL;DR: An optimized k-means implementation on the graphics processing unit (GPU) is presented, demonstrating a maximum 14x speed increase to a fully SIMD optimized CPU implementation.