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Topic modeling

Using Jupyter from KNIME: embedding documentsThis workflow demonstrates the use of functionality defined in a Jupyter notebook from inside of KNIME. Afterbuilding a topic model for a set of documents, we use a Python function from a Jupyter notebook to perform t-SNEembedding of the documents into a 2D space. As a final step we do an interactive visualization to allow exploringthe results.The documents used are taken from the Fun with Tags post on the KNIME Blog: https://www.knime.com/blog/fun-with-tagsKNIME Extensions required: - Textprocessing - KNIME Python ScriptingThe Python Scripting integration needs to be configured to use a Python environment that has scikit-learn andjupyter installed. Load data and build topic model Visualize results t-SNE embedding Read documentsNode 947 Topic Extractor(Parallel LDA) Color Manager ReferenceRow Filter Joiner Interactivevisualization Table Reader Pick 10 randomqueries Preprocessdocuments t-SNE (L. Jonsson) Using Jupyter from KNIME: embedding documentsThis workflow demonstrates the use of functionality defined in a Jupyter notebook from inside of KNIME. Afterbuilding a topic model for a set of documents, we use a Python function from a Jupyter notebook to perform t-SNEembedding of the documents into a 2D space. As a final step we do an interactive visualization to allow exploringthe results.The documents used are taken from the Fun with Tags post on the KNIME Blog: https://www.knime.com/blog/fun-with-tagsKNIME Extensions required: - Textprocessing - KNIME Python ScriptingThe Python Scripting integration needs to be configured to use a Python environment that has scikit-learn andjupyter installed. Load data and build topic model Visualize results t-SNE embedding Read documentsNode 947Topic Extractor(Parallel LDA) Color Manager ReferenceRow Filter Joiner Interactivevisualization Table Reader Pick 10 randomqueries Preprocessdocuments t-SNE (L. Jonsson)

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: jeany
Created at: 2018-06-13
On NodePit since: 2019-10-03
Last update: 2024-12-24
Created with KNIME version: v4.0.1

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