02_​Topic_​Scoring_​Example

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The Topic Scorer (Labs) verified component implements an experimental score for semantic coherence, exclusivity and
similarity/distance of topics of one or multiple models.

Read more on the component pages at knime.com/verified-components. References are also available below in this workflow page.

URL: “PoliBlogs08” data set by Eisenstein and Xing 2010 https://dl.acm.org/doi/10.5555/1870658.1870782
URL: Optimizing semantic coherence in topic models - Mimno et al 2011, Proceedings of the Conference on Empirical Methods in Natural Language Processing 2011 https://dl.acm.org/doi/10.5555/2145432.2145462
URL: Summarizing topical content with word frequency and exclusivity - Bischof and Airoldi (2012), Proceedings of the 29th International Coference on International Conference on Machine Learning https://dl.acm.org/doi/10.5555/3042573.3042578
URL: Topic Scorer (Labs) - KNIME Community Hub https://hub.knime.com/-/spaces/-/latest/~5_W2h2g6hBY_M0Bc/
URL: Verified Components project - knime.com https://www.knime.com/verified-components

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• Column Rename77 ×
• Column Filter49 ×
• GroupBy46 ×
• Inject Variables (Data)31 ×
• String Manipulation30 ×
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