Visualizing Temporal Topic Embeddings with a Compass

Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a meaningful embedding space where changes in word usage and documen...

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Veröffentlicht in:	IEEE transactions on visualization and computer graphics Jg. 31; H. 1; S. 272 - 282
Hauptverfasser:	Palamarchuk, Daniel, Williams, Lemara, Mayer, Brian, Danielson, Thomas, Faust, Rebecca, Deschaine, Larry, North, Chris
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2025
Schlagworte:	Cluster analysis Clustering algorithms Compass Dynamic topic modeling Electronic mail High dimensional data Streams Training Vectors Visualization
ISSN:	1077-2626, 1941-0506, 1941-0506
Online-Zugang:	Volltext
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