Semantic Document Maps and Clusters
Channel: Orange Data Mining
Date: 2022-06-30

Text mining with Orange. Learn about Orange components that we have designed for analysis of text. The series includes tutorials on loading of documents, construction of word clouds, keyword extraction, visualisation of document and word maps, text-based classification, and many other topics.

In the series, we present and analyse a repository of proposals to the Slovene government that are available at http://file.biolab.si/text-semantics/data. Some of the original documents were written in the Slovene language, and we machine-translated them into English. An example of such translations is a sample of proposals at http://file.biolab.si/text-semantics/data/proposals-to-government-1k.

In this video, we show how to: 
Import data from a repository into Orange(Import Documents widget), 
How to preprocess text, to make sure that the program can process it (PreprocessText widget)
Embed documents and reduce the number of vector dimensions of the embedded documents (Document Embedding and t-SNE widgets)
Find clusters of related documents in a t-SNE map (t-SNE widget)
Explore content of the (related) documents (Word Cloud and Corpus Viewer widgets). 


Download Orange from:
https://orangedatamining.com/download/

License: GNU GPL + CC
Music by: Damjan Jović - Dravlje Rec
Website: https://orangedatamining.com
Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana