2 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
FDive: Learning Relevance Models using Pattern-based Similarity Measures
Frederik L. Dennig, Tom Polk, Zudi Lin +3
The detection of interesting patterns in large high-dimensional datasets is difficult because of their dimensionality and pattern complexity. Therefore, analysts require automated…