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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.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…