HSUM-HC:基于bert的隐聚集与层次分类器的越南语面向方面的情感分析

Tri Cong-Toan Tran, Thien Phu Nguyen, Thanh Le
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引用次数: 2

摘要

基于情感分析(ABSA)旨在识别顾客评论或评论中特定方面的情感极性,是社交倾听研究中一个有吸引力的课题。在本文中,我们将PhoBert的顶层隐藏层集成到一个层次分类器中,构建了一个专门的模型,利用这些组件为ABSA任务提出了一种有效的分类方法。我们在越南语的两个公共数据集上评估了我们的模型的性能,结果表明我们的实现在两个数据集上都优于以前的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HSUM-HC: Integrating Bert-based hidden aggregation to hierarchical classifier for Vietnamese aspect-based sentiment analysis
Based Sentiment Analysis (ABSA), which aims to identify sentiment polarity towards specific aspects in customers’ comments or reviews, has been an attractive topic of research in social listening. In this paper, we construct a specialized model utilizing PhoBert’s top-level hidden layers integrated into a hierarchical classifier, taking advantage of these components to propose an effective classification method for ABSA task. We evaluated our model’s performance on two public datasets in Vietnamese and the results show that our implementation outperforms previous models on both datasets.
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