@inproceedings{zirikly-etal-2016-gw-lt3,
title = "The {GW}/{LT}3 {V}ar{D}ial 2016 Shared Task System for Dialects and Similar Languages Detection",
author = "Zirikly, Ayah and
Desmet, Bart and
Diab, Mona",
editor = {Nakov, Preslav and
Zampieri, Marcos and
Tan, Liling and
Ljube{\v{s}}i{\'c}, Nikola and
Tiedemann, J{\"o}rg and
Malmasi, Shervin},
booktitle = "Proceedings of the Third Workshop on {NLP} for Similar Languages, Varieties and Dialects ({V}ar{D}ial3)",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-4804",
pages = "33--41",
abstract = "This paper describes the GW/LT3 contribution to the 2016 VarDial shared task on the identification of similar languages (task 1) and Arabic dialects (task 2). For both tasks, we experimented with Logistic Regression and Neural Network classifiers in isolation. Additionally, we implemented a cascaded classifier that consists of coarse and fine-grained classifiers (task 1) and a classifier ensemble with majority voting for task 2. The submitted systems obtained state-of-the art performance and ranked first for the evaluation on social media data (test sets B1 and B2 for task 1), with a maximum weighted F1 score of 91.94{\%}.",
}
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%0 Conference Proceedings
%T The GW/LT3 VarDial 2016 Shared Task System for Dialects and Similar Languages Detection
%A Zirikly, Ayah
%A Desmet, Bart
%A Diab, Mona
%Y Nakov, Preslav
%Y Zampieri, Marcos
%Y Tan, Liling
%Y Ljubešić, Nikola
%Y Tiedemann, Jörg
%Y Malmasi, Shervin
%S Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F zirikly-etal-2016-gw-lt3
%X This paper describes the GW/LT3 contribution to the 2016 VarDial shared task on the identification of similar languages (task 1) and Arabic dialects (task 2). For both tasks, we experimented with Logistic Regression and Neural Network classifiers in isolation. Additionally, we implemented a cascaded classifier that consists of coarse and fine-grained classifiers (task 1) and a classifier ensemble with majority voting for task 2. The submitted systems obtained state-of-the art performance and ranked first for the evaluation on social media data (test sets B1 and B2 for task 1), with a maximum weighted F1 score of 91.94%.
%U https://aclanthology.org/W16-4804
%P 33-41
Markdown (Informal)
[The GW/LT3 VarDial 2016 Shared Task System for Dialects and Similar Languages Detection](https://aclanthology.org/W16-4804) (Zirikly et al., VarDial 2016)
ACL