@inproceedings{piasecki-etal-2017-recognition,
title = "Recognition of Genuine {P}olish Suicide Notes",
author = "Piasecki, Maciej and
M{\l}ynarczyk, Ksenia and
Koco{\'n}, Jan",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
month = sep,
year = "2017",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://doi.org/10.26615/978-954-452-049-6_076",
doi = "10.26615/978-954-452-049-6_076",
pages = "583--591",
abstract = "In this article we present the result of the recent research in the recognition of genuine Polish suicide notes (SNs). We provide useful method to distinguish between SNs and other types of discourse, including counterfeited SNs. The method uses a wide range of word-based and semantic features and it was evaluated using Polish Corpus of Suicide Notes, which contains 1244 genuine SNs, expanded with manually prepared set of 334 counterfeited SNs and 2200 letter-like texts from the Internet. We utilized the algorithm to create the class-related sense dictionaries to improve the result of SNs classification. The obtained results show that there are fundamental differences between genuine SNs and counterfeited SNs. The applied method of the sense dictionary construction appeared to be the best way of improving the model.",
}
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%0 Conference Proceedings
%T Recognition of Genuine Polish Suicide Notes
%A Piasecki, Maciej
%A Młynarczyk, Ksenia
%A Kocoń, Jan
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F piasecki-etal-2017-recognition
%X In this article we present the result of the recent research in the recognition of genuine Polish suicide notes (SNs). We provide useful method to distinguish between SNs and other types of discourse, including counterfeited SNs. The method uses a wide range of word-based and semantic features and it was evaluated using Polish Corpus of Suicide Notes, which contains 1244 genuine SNs, expanded with manually prepared set of 334 counterfeited SNs and 2200 letter-like texts from the Internet. We utilized the algorithm to create the class-related sense dictionaries to improve the result of SNs classification. The obtained results show that there are fundamental differences between genuine SNs and counterfeited SNs. The applied method of the sense dictionary construction appeared to be the best way of improving the model.
%R 10.26615/978-954-452-049-6_076
%U https://doi.org/10.26615/978-954-452-049-6_076
%P 583-591
Markdown (Informal)
[Recognition of Genuine Polish Suicide Notes](https://doi.org/10.26615/978-954-452-049-6_076) (Piasecki et al., RANLP 2017)
ACL
- Maciej Piasecki, Ksenia Młynarczyk, and Jan Kocoń. 2017. Recognition of Genuine Polish Suicide Notes. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 583–591, Varna, Bulgaria. INCOMA Ltd..