使用机器学习概念分析客户评论并预测产品的未来发布

P. R. Sabapathi, K. Kaliyamurthie
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引用次数: 0

摘要

客户评论采用非结构化形式和自然语言。为了使数据结构化,使用了情感分析等自然语言处理算法。该方法是提取评论在状态中是积极的、消极的还是中立的。情感分析用于捕捉每个产品对特定产品的意见和感受。建议工作的主要目标是预测产品的未来版本。对于预测,添加了机器学习算法和情感分析,以提供更好的性能。在本文提出的工作中,首先对数据进行采集,然后对数据进行预处理。其次,采用维德情感分析对顾客评论进行分析,提取特征;随机森林分类器通过使用决策树算法预测产品的未来发布来提高性能。与现有的工作相比,建议的工作提供并改进了性能结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Customer Review and Predicting Future Release of the Product using machine learning concepts
The customer reviews are in unstructured form and natural language. To make data structured, natural language processing algorithms like sentimental analysis are used. This method is to extract whether the reviews are positive, negative, or neutral in the state. Sentimental analysis is used to capture each product's opinions and feelings about the particular product. The main objective of the proposed work is to predict the future release of the product. For prediction, machine learning algorithms along with sentimental analysis are added that provide better performance. In the proposed work, firstly the data is collected, and then it is preprocessed. Secondly, Vader sentiment analysis is implemented for analyzing the customer reviews followed by extracting the features. Random forest classifiers were carried out for improving the performance pursued by predicting the future release of the product using a decision tree algorithm. The proposed work provides and improves performance results compared to the existing works.
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