11 citations · 11 across the 2 of their papers we have counts for
3 papers
cs.CL2024
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…
cs.LG2024
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…
cs.CL2023★ 11 cited
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…