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Analyzing Customer Sentiments Using Machine Learning Techniques to Improve Business Performance

机译:利用机器学习技术分析客户情绪,提高业务绩效

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摘要

In today’s digital world, advancement in machine learning has changed the traditional perspective towards business analysis. Orthodox business analysts did not consider customer reviews as cost-effective input for analysis because earlier fetching customer reviews was costly. The emergence of the internet turned the whole world upside down. Now, the customer’s sentiment analysis is the new friend of all business analysts. In this paper, we will be doing a comparative study between the two methods. One in which we use usual parameters like average rating, average review counts. In second, we use a text review as a parameter for sentiment classification. The effectiveness of these methods is evaluated, and the optimal model is selected.
机译:在当今的数字世界中,机器学习的进步改变了传统的业务分析的视角。东正教业务分析师没有考虑客户评论作为经济效益的分析投入,因为早些时候提取的客户评论昂贵。互联网的出现使整个世界颠倒了。现在,客户的情感分析是所有商业分析师的新朋友。在本文中,我们将在两种方法之间进行比较研究。我们使用平均评级等常用参数的一个,平均审查数。第二,我们使用文本审查作为情感分类的参数。评估这些方法的有效性,选择了最佳模型。

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