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Combining Lexicon-Based and Learning-Based Methods for Sentiment Analysis for Product Reviews in Vietnamese Language

机译:结合基于词典和基于学习的方法对越南语产品评论进行情感分析

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Social media websites are a major hub for users to express their opinions online. Businesses spend an enormous amount of time and money to understand their customer opinions about their products and services. Sentiment analysis which is also called opinion mining, involves in building a system to collect and examine opinions about the product made in blog posts, comments, or reviews. In this paper, we propose a framework for sentiment analysis based on combining lexicon-based and learning-based methods for product review sentiment analysis in Vietnamese language. Text analytics, Linguistic analysis and Vietnamese emotional dictionary were built, proposing features which adapted with the language was proposed. The experimental show that our system has very well performance when combine advantage of lexicon-based and learning based and can be applied in online systems for sentiment analysis product reviews.
机译:社交媒体网站是用户在线表达意见的主要枢纽。企业花费大量时间和金钱来了解客户对其产品和服务的看法。情感分析(也称为观点挖掘)涉及构建一个系统来收集和检查博客文章,评论或评论中有关产品的观点。在本文中,我们提出了一个基于情感词典和基于学习的方法相结合的越南语产品评论情感分析的情感分析框架。建立了文本分析,语言分析和越南语情感词典,并提出了与语言相适应的功能。实验表明,结合基于词典和基于学习的优势,我们的系统具有很好的性能,可在在线系统中用于情感分析产品评论。

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