论文标题
Nayel在Semeval-2020任务12：基于TF/IDF基于Arabic Tweet的自动进攻语言检测方法
NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets
论文作者
论文摘要
在本文中，我们介绍提交给“ Semeval-2020任务12”的系统。拟议的系统旨在自动确定阿拉伯语推文中的进攻性语言。基于机器学习的方法已用于设计我们的系统。我们以优化算法实现了具有随机梯度下降（SGD）的线性分类器。我们的模型报告了开发集和测试集的84.20％，81.82％的F1得分。最佳性能的系统和上升等级中的系统分别在测试集上报告了90.17％和44.51％的F1分数。
In this paper, we present the system submitted to "SemEval-2020 Task 12". The proposed system aims at automatically identify the Offensive Language in Arabic Tweets. A machine learning based approach has been used to design our system. We implemented a linear classifier with Stochastic Gradient Descent (SGD) as optimization algorithm. Our model reported 84.20%, 81.82% f1-score on development set and test set respectively. The best performed system and the system in the last rank reported 90.17% and 44.51% f1-score on test set respectively.
