Comparative Exploration Of Prediction Algorithms For Sentiment Analysis Using NLP

机译：基于NLP的情感分析预测算法的比较探索

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Recently, enormous amount of online or e-commerce reviews that reveal the opinion of the clients, benefit designers and consumers. But, with excessive progress of product attributes and reviews which are getting more assorted, the conventional sentiment analysis about the general emotional tendency is unable to fulfill the requirements of customers and manufacturers. Customers expect to acquire analysis outcomes of goal features whereas the manufacturers expect to master weaknesses and strengths of products plus also the customers' taste. The proposed study takes the raw reviews, cleans them to remove the stop words and then runs various prediction algorithms, the results of which are then evaluated to come to a conclusion.

机译：最近，巨大的在线或电子商务评论，揭示了客户的意见，利益设计师和消费者。但是，由于产品属性和评论的过度进展，越来越各种各样的，传统情绪分析普遍情绪倾向无法满足客户和制造商的要求。客户希望获得目标特征的分析结果，而制造商希望掌握产品的弱点和优势，也是客户的味道。拟议的研究采用RAUG评论，清理它们以删除停止单词，然后运行各种预测算法，然后评估其结果得出结论。

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《International Conference on Computer Communication and Informatics》|2019年|1-6|共6页
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Umid Kumar Dey; Alaa Noor;
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Sentiment analysis; Sparse matrices; Predictive models; Prediction algorithms; Machine learning; Informatics;

机译：情感分析;稀疏矩阵;预测模型;预测算法;机器学习;信息学;

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Comparative Exploration Of Prediction Algorithms For Sentiment Analysis Using NLP

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