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taishi-i / nagisa

A Japanese tokenizer based on recurrent neural networks
https://huggingface.co/spaces/taishi-i/nagisa-demo
MIT License
379 stars 22 forks source link

About referecnce this library #22

Closed mrpeerat closed 4 years ago

mrpeerat commented 4 years ago

I want to citation this library, and I want to know you have any paper or journal to read more about this library work or Bibtext for citation?

taishi-i commented 4 years ago

Hi @mrpeerat, thank you for using this tool. Please cite the following BibTeX.

@misc{ikeda2018nagisa,
  author = {Taishi Ikeda},
  title = {nagisa: A Japanese tokenizer based on recurrent neural networks},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github. com/taishi-i/nagisa}},
}

I'm sorry that I publish the paper about this tool only in Japanese. So, if you want to know about word segmentation method, please refer to this attach file Japanese_Word_Segmentation_using_Character-level_Recurrent_Networks_with_Dictionary_Information.pdf.

Please let me know when your paper is published. Thank you.

mrpeerat commented 4 years ago

Thank you so much

wannaphong commented 3 years ago

@taishi-i Hello. This paper is Domain Adaptation of Thai Word Segmentation Models using Stacked Ensemble at https://aclanthology.org/2020.emnlp-main.315/.

Thank you.

mrpeerat commented 3 years ago

@taishi-i Hello. This paper is Domain Adaptation of Thai Word Segmentation Models using Stacked Ensemble at https://aclanthology.org/2020.emnlp-main.315/.

Thank you.

Also, Handling Cross- and Out-of-Domain Samples in Thai Word Segmentation https://aclanthology.org/2021.findings-acl.86/