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

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Abstract

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
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