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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Conference papers
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01910611
Contributor : Pascal Poncelet <>
Submitted on : Thursday, November 1, 2018 - 3:18:14 PM
Last modification on : Wednesday, April 3, 2019 - 1:10:49 AM
Long-term archiving on : Saturday, February 2, 2019 - 1:33:21 PM

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  • HAL Id : lirmm-01910611, version 1

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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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