11 citations · 17 across the 4 of their papers we have counts for
4 papers
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text Spatializations
Daniel Atzberger, Tim Cech, Willy Scheibel +3
The semantic similarity between documents of a text corpus can be visualized using map-like metaphors based on two-dimensional scatterplot layouts. These layouts result from a dime…
Standardness Clouds Meaning: A Position Regarding the Informed Usage of Standard Datasets
Tim Cech, Ole Wegen, Daniel Atzberger +3
Standard datasets are frequently used to train and evaluate Machine Learning models. However, the assumed standardness of these datasets leads to a lack of in-depth discussion on h…
Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text Spatialization
Daniel Atzberger, Tim Cech, Willy Scheibel +4
Topic models are a class of unsupervised learning algorithms for detecting the semantic structure within a text corpus. Together with a subsequent dimensionality reduction algorith…
Tooling for Time- and Space-efficient git Repository Mining
Fabian Heseding, Willy Scheibel, Jürgen Döllner
Software projects under version control grow with each commit, accumulating up to hundreds of thousands of commits per repository. Especially for such large projects, the traversal…