@inproceedings{shnarch-etal-2022-label,
    title = "Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours",
    author = "Shnarch, Eyal  and
      Halfon, Alon  and
      Gera, Ariel  and
      Danilevsky, Marina  and
      Katsis, Yannis  and
      Choshen, Leshem  and
      Santillan Cooper, Martin  and
      Epelboim, Dina  and
      Zhang, Zheng  and
      Wang, Dakuo  and
      Yip, Lucy  and
      Ein-Dor, Liat  and
      Dankin, Lena  and
      Shnayderman, Ilya  and
      Aharonov, Ranit  and
      Li, Yunyao  and
      Liberman, Naftali  and
      Levin Slesarev, Philip  and
      Newton, Gwilym  and
      Ofek-Koifman, Shila  and
      Slonim, Noam  and
      Katz, Yoav",
    editor = "Che, Wanxiang  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/moar-dois/2022.emnlp-demos.16/",
    doi = "10.18653/v1/2022.emnlp-demos.16",
    pages = "159--168",
    abstract = "Label Sleuth is an open source platform for building text classifiers which does not require coding skills nor machine learning knowledge.- Project website: [\url{https://www.label-sleuth.org/}](\url{https://www.label-sleuth.org/})- Link to screencast video: [\url{https://vimeo.com/735675461}](\url{https://vimeo.com/735675461}){\#}{\#}{\#} AbstractText classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a classifier generally requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier we introduce *Label Sleuth*, a free open source system for labeling and creating text classifiers. This system is unique for: - being a no-code system, making NLP accessible for non-experts. - guiding its users throughout the entire labeling process until they obtain their desired classifier, making the process efficient - from cold start to a classifier in a few hours. - being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will widen the utilization of NLP models."
}