Topic Detection LDA: Summarizing Romeo & Juliet or cataloging News

The workflow shows two examples for the Topic Extrator (Parallel LDA) node.

The first 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.

The second workflow catalogs news, performing similar steps.