孟加拉语文本情感分析的混合框架

Md. Motaleb Hossen Manik, Fabliha Haque, M. Hashem, Md. Ahsan Habib, Md. Zabirul Islam, Tanim Ahmed
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引用次数: 0

摘要

由于社交媒体和网络上用户互动的兴起,情感分析从多个角度获得了极大的兴趣。它通过分析对可用选项的评论来帮助人们选择最好的服务或产品。由于目前需求的增加,孟加拉情绪分析在整个研究界得到了普及。然而,几乎所有的孟加拉人情绪分析研究都集中在单一的方法上,这在这一领域造成了研究空白。因此,本文提出了一个混合框架,结合机器学习和基于规则的方法对孟加拉语文本进行情感分析。本研究从机器学习方法开始,然后将其中间结果与新提出的基于规则的方法的结果相结合,以产生最终的评论情绪。实验分析表明,该混合框架的准确率为95.54%,优于以往的混合框架,保证了其有效性。
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A Hybrid Framework for Sentiment Analysis from Bangla Texts
Sentiment analysis has gained significant interest from multiple perspectives due to the rise of user interactions on social media and the web. It assists people in choosing the best service or product by analyzing the reviews of available options. Due to the current rise in demand, Bangla sentiment analysis has gained popularity throughout the research community. However, almost all Bangla sentiment analysis research has focused on a single approach, which has created a research gap in this domain. Therefore, this paper proposes a hybrid framework to perform sentiment analysis on Bangla texts that combines machine learning and a rule-based approach. This research starts with the machine learning approach and then integrates its intermediate result with the result of a newly proposed rule-based approach to produce the final sentiment of reviews. The experimental analysis states that the proposed hybrid framework outperforms the previous works with an accuracy of 95.54%, which assures its efficacy.
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