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DGurgurov/slovak_sa

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Permissive or share-alike

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 250a731
Licence files: No licence file at the top level of the repositoryEvidence: file list at 250a731
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Tasks

text-classification

Citation text from the card

@inproceedings{pecar-etal-2019-improving,
    title = "Improving Sentiment Classification in {S}lovak Language",
    author = "Pecar, Samuel  and
      Simko, Marian  and
      Bielikova, Maria",
    editor = "Erjavec, Toma{\v{z}}  and
      Marci{\'n}czuk, Micha{\l}  and
      Nakov, Preslav  and
      Piskorski, Jakub  and
      Pivovarova, Lidia  and
      {\v{S}}najder, Jan  and
      Steinberger, Josef  and
      Yangarber, Roman",
    booktitle = "Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-3716",
    doi = "10.18653/v1/W19-3716",
    pages = "114--119",
    abstract = "Using different neural network architectures is widely spread for many different NLP tasks. Unfortunately, most of the research is performed and evaluated only in English language and minor languages are often omitted. We believe using similar architectures for other languages can show interesting results. In this paper, we present our study on methods for improving sentiment classification in Slovak language. We performed several experiments for two different datasets, one containing customer reviews, the other one general Twitter posts. We show comparison of performance of different neural network architectures and also different word representations. We show that another improvement can be achieved by

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dataset_licence({ "id": "DGurgurov/slovak_sa" })
signal: "permissive"
stated_licence: "mit"
sources: 0