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Readitopics: Make Your Topic Models Readable via Labeling and Browsing

Abstract : Readitopics provides a new tool for browsing a textual corpus that showcases several recent work for labeling topic models and estimating topic coherence. We will demonstrate the potential of these techniques to get a deeper understanding of the topics that structure different kinds of datasets. This tool is provided as a Web demo but it can be easily installed to experiment with your own dataset. It can be further extended to deal with more advanced topic modeling techniques.
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Submitted on : Thursday, November 1, 2018 - 3:18:14 PM
Last modification on : Tuesday, March 17, 2020 - 2:56:00 AM
Document(s) archivé(s) le : Saturday, February 2, 2019 - 1:33:21 PM


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  • HAL Id : lirmm-01910611, version 1


Julien Velcin, Antoine Gourru, Erwan Giry-Fouquet, Christophe Gravier, Mathieu Roche, et al.. Readitopics: Make Your Topic Models Readable via Labeling and Browsing. IJCAI: International Joint Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden. ⟨lirmm-01910611⟩



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