Readitopics: Make Your Topic Models Readable via Labeling and Browsing

Julien Velcin, Antoine Gourru, Erwan Giry-Fouquet, Christophe Gravier, Mathieu Roche, Pascal Poncelet

IJCAI 2018 pp. 5874-5876

doi:10.24963/IJCAI.2018/867 /ijcai/2018/velcin2018ijcai-readitopics/

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.

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Cite

Text

Velcin et al. "Readitopics: Make Your Topic Models Readable via Labeling and Browsing." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/867

Markdown

[Velcin et al. "Readitopics: Make Your Topic Models Readable via Labeling and Browsing." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/velcin2018ijcai-readitopics/) doi:10.24963/IJCAI.2018/867

BibTeX

@inproceedings{velcin2018ijcai-readitopics,
  title     = {{Readitopics: Make Your Topic Models Readable via Labeling and Browsing}},
  author    = {Velcin, Julien and Gourru, Antoine and Giry-Fouquet, Erwan and Gravier, Christophe and Roche, Mathieu and Poncelet, Pascal},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {5874-5876},
  doi       = {10.24963/IJCAI.2018/867},
  url       = {https://mlanthology.org/ijcai/2018/velcin2018ijcai-readitopics/}
}