Readitopics: Make Your Topic Models Readable via Labeling and Browsing
Readitopics: Make Your Topic Models Readable via Labeling and Browsing
Julien Velcin, Antoine Gourru, Erwan Giry-Fouquet, Christophe Gravier, Mathieu Roche, Pascal Poncelet
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Demos. Pages 5874-5876.
https://doi.org/10.24963/ijcai.2018/867
Readitopics provides a new tool for browsing a textual corpus that showcases several recent work on topic labeling and topic coherence. We demonstrate the potential of these techniques to get a deeper understanding of the topics that structure different datasets. This tool is provided as a Web demo but it can be installed to experiment with your own dataset. It can be further extended to deal with more advanced topic modeling techniques.
Keywords:
Natural Language Processing: NLP Applications and Tools
Natural Language Processing: Sentiment Analysis and Text Mining