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08 Topic Detection

08 Topic Detection
Exercise: Topic DetectionIn this exercise you'll use the LDA algorithm for topic detection in a document corpus. 1) Execute the Preprocessed Documents metanode. It preprocesses the five classifiers of the Microsoft RSS feeds. 2) Perform topic detection on the document corpus. Select 5 topics and 5 words per topic.3) Color the keywords in the middle output of the Topic Extractor (Parallel LDA) node by their topic ID4) Show the keywords in a word cloud, each topic with a different color. Use the weight of each word as the size column. 5) Given the following courses, how would you match them to the topics?- cybersecurity topic_0- visual studio topic_1- growth topic_2- other topic_3- expectations topic_4 5 topics &5 wordsby topicNode 44 PreprocessedDocuments Topic Extractor(Parallel LDA) Color Manager Tag Cloud Exercise: Topic DetectionIn this exercise you'll use the LDA algorithm for topic detection in a document corpus. 1) Execute the Preprocessed Documents metanode. It preprocesses the five classifiers of the Microsoft RSS feeds. 2) Perform topic detection on the document corpus. Select 5 topics and 5 words per topic.3) Color the keywords in the middle output of the Topic Extractor (Parallel LDA) node by their topic ID4) Show the keywords in a word cloud, each topic with a different color. Use the weight of each word as the size column. 5) Given the following courses, how would you match them to the topics?- cybersecurity topic_0- visual studio topic_1- growth topic_2- other topic_3- expectations topic_4 5 topics &5 wordsby topicNode 44PreprocessedDocuments Topic Extractor(Parallel LDA) Color Manager Tag Cloud

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Created by: Lada.Rudnitckaia
Created at: 2020-07-31
On NodePit since: 2022-03-29
Last update: 2024-12-17
Created with KNIME version: v4.5.2
Tags: NLPText miningText processingNatural Language Processingldatopic detection

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