团队YahyaD11在Mowjaz多主题标签任务

Yahya Daqour
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引用次数: 0

摘要

本文重点介绍了我使用双向门控循环单元(Bi-GRU)参加ICICS 2021竞赛Mowjaz多主题标签任务的情况。该模型主要用于根据文章内容中的主题对文章进行分类。Mowjaz的主题被分为十个类别,一篇文章可以被归类到它所涵盖的许多主题下。在评估中,我们将Mowjaz多主题标注任务视为多分类任务,并使用Unigram模型提取特征来训练神经网络分类器。结果我的方法准确率达到0.8232,排名第8。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Team YahyaD11 at the Mowjaz Multi-Topic Labelling Task
This paper focuses of my enrollment in ICICS 2021 Competition Mowjaz Multi-Topic Labelling Task using Bidirectional Gated Recurrent Unit (Bi-GRU). The model is basically used to classify articles based on their topics that are present within its content. Mowjaz’s topic are classified into ten categories and an article can be classified as under as many topics as it covers. In the evaluation, we regard the Mowjaz Multi-Topic labelling task as multi-classification task and use Unigram models to extract features to train a neural network classifier. In the result, the accuracy of my method reached 0.8232, ranking 8th .
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