Topic Detection LDA

This workflow extracts topics from the "Romeo & Juliet" epub book using the Topic Extractor (Parallel LDA) node. It reads textual data from a table and converts them into documents. The documents are then preprocessed, i.e. tagged, filtered, lemmatized, etc. After that, the Topic Extractor node can be applied to the preprocessed documents. However, the node requires users to input the number of topics that should be extracted beforehand. After pre-processing, the Topic Extractor node can be executed and a tag cloud is created to visualize the topics' terms.

TAGS: topic detection, text summarization, LDA, text processing

Topic Detection LDA

 

Resources

EXAMPLES Server: 08_Other_Analytics_Types/01_Text_Processing/25_Topic_Detection_LDA08_Other_Analytics_Types/01_Text_Processing/25_Topic_Detection_LDA*
Download a zip-archive

 

 


* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually