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01_​Topic_​Detection Clustering

01_Topic Detection Clustering
Topic Detection Clustering After classic pre-processing (in streaming mode!) we: - extract the document keywords with a KeyGraph Keyword Extractor node. - we display the words making the protottype of each cluster into a word cloud. The word clouds are displayed in the interactive view of component Cluster 0-9.Note. We limit the score of the keywords to 5, in order to avoid an uncontrolled growth of the number of columns feeding the clustering algorithm. 5 keywords perdocumentBinary vectorcreation80/205 keywords perdocument Keygraph KeywordExtractor Streaming TextPreprocessing StreamingEnrichment k-Means Document Vector StreamingReading Data Cluster Assigner Top keyword/ clutser Clusters 0-9 Remove smallclusters Partitioning DocumentVector Applier Keygraph KeywordExtractor Topic Detection Clustering After classic pre-processing (in streaming mode!) we: - extract the document keywords with a KeyGraph Keyword Extractor node. - we display the words making the protottype of each cluster into a word cloud. The word clouds are displayed in the interactive view of component Cluster 0-9.Note. We limit the score of the keywords to 5, in order to avoid an uncontrolled growth of the number of columns feeding the clustering algorithm. 5 keywords perdocumentBinary vectorcreation80/205 keywords perdocumentKeygraph KeywordExtractor Streaming TextPreprocessing StreamingEnrichment k-Means Document Vector StreamingReading Data Cluster Assigner Top keyword/ clutser Clusters 0-9 Remove smallclusters Partitioning DocumentVector Applier Keygraph KeywordExtractor

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Created by: andisadewi
Created at: 2016-08-31
On NodePit since: 2021-03-10
Last update: 2024-04-26
Created with KNIME version: v4.5.0
Tags: BooksText MiningFrom Words To Wisdom

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