@inproceedings{miranda-jimenez-etal-2020-ingeotec,
title = "{INGEOTEC} at {S}em{E}val-2020 Task 12: Multilingual Classification of Offensive Text",
author = "Miranda-Jim{\'e}nez, Sabino and
Tellez, Eric S. and
Graff, Mario and
Moctezuma, Daniela",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.262",
doi = "10.18653/v1/2020.semeval-1.262",
pages = "1992--1997",
abstract = "This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achieved with EvoMSA, which is a multilingual and domain-independent architecture that combines the prediction from different knowledge sources to solve text classification problems.",
}
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<abstract>This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achieved with EvoMSA, which is a multilingual and domain-independent architecture that combines the prediction from different knowledge sources to solve text classification problems.</abstract>
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%0 Conference Proceedings
%T INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text
%A Miranda-Jiménez, Sabino
%A Tellez, Eric S.
%A Graff, Mario
%A Moctezuma, Daniela
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F miranda-jimenez-etal-2020-ingeotec
%X This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achieved with EvoMSA, which is a multilingual and domain-independent architecture that combines the prediction from different knowledge sources to solve text classification problems.
%R 10.18653/v1/2020.semeval-1.262
%U https://aclanthology.org/2020.semeval-1.262
%U https://doi.org/10.18653/v1/2020.semeval-1.262
%P 1992-1997
Markdown (Informal)
[INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text](https://aclanthology.org/2020.semeval-1.262) (Miranda-Jiménez et al., SemEval 2020)
ACL