TY - GEN
T1 - TUVD team at SemEval-2019 task 6
T2 - 13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
AU - Shushkevich, Elena
AU - Cardiff, John
AU - Rosso, Paolo
N1 - Publisher Copyright:
© 2019 Association for Computational Linguistics
PY - 2019
Y1 - 2019
N2 - This article presents our approach for detecting a target of offensive messages in Twitter, including Individual, Group and Others classes. The model we have created is an ensemble of simpler models, including Logistic Regression, Naive Bayes, Support Vector Machine and the interpolation between Logistic Regression and Naive Bayes with 0.25 coefficient of interpolation. The model allows us to achieve 0.547 macro F1-score.
AB - This article presents our approach for detecting a target of offensive messages in Twitter, including Individual, Group and Others classes. The model we have created is an ensemble of simpler models, including Logistic Regression, Naive Bayes, Support Vector Machine and the interpolation between Logistic Regression and Naive Bayes with 0.25 coefficient of interpolation. The model allows us to achieve 0.547 macro F1-score.
UR - https://www.scopus.com/pages/publications/85093464923
U2 - 10.18653/v1/s19-2135
DO - 10.18653/v1/s19-2135
M3 - Conference contribution
AN - SCOPUS:85093464923
T3 - NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop
SP - 770
EP - 774
BT - NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop
PB - Association for Computational Linguistics (ACL)
Y2 - 6 June 2019 through 7 June 2019
ER -