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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 agenda texts of five instructor-led courses. 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?- L4-BD Introduction to Big Data with KNIME Analytics Platform- L4-DL Introduction to Deep Learning- L4-CH Introduction to Working with Chemical Data- L4-ML Introduction to Machine Learning Algorithms- L4-TS Introduction to Time Series Analysis Node 42Node 43Node 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 agenda texts of five instructor-led courses. 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?- L4-BD Introduction to Big Data with KNIME Analytics Platform- L4-DL Introduction to Deep Learning- L4-CH Introduction to Working with Chemical Data- L4-ML Introduction to Machine Learning Algorithms- L4-TS Introduction to Time Series Analysis Node 42Node 43Node 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: 2023-07-17
Last update: 2024-11-17
Created with KNIME version: v4.7.4

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