Topic Scoring with Verified Components

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.

External resources

• “PoliBlogs08” data set by Eisenstein and Xing 2010
• Optimizing semantic coherence in topic models - Mimno et al 2011, Proceedings of the Conference on Empirical Methods in Natural Language Processing 2011
• Summarizing topical content with word frequency and exclusivity - Bischof and Airoldi (2012), Proceedings of the 29th International Coference on International Conference on Machine Learning
• Topic Scorer (Labs) - KNIME Community Hub
• Verified Components project - knime.com