大型亚马逊产品评论的情感分析

2018 IEEE International Conference on Innovative Research and Development (ICIRD) Pub Date : 2018-05-11 DOI:10.1109/ICIRD.2018.8376299

Tanjim Ul Haque, Nudrat Nawal Saber, F. Shah

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引用次数: 143

摘要

我们现在看到的世界正变得越来越数字化。在这个数字化的世界里，电子商务正在占据主导地位，因为它使顾客不必走出家门就能买到产品。如今，人们越来越依赖在线产品，因此评论的重要性越来越高。为了选择产品，客户需要通过数千条评论来了解产品。但在这个机器学习蓬勃发展的时代，如果使用一个模型来分化这些评论并从中学习，那么浏览数千条评论会容易得多。我们使用监督学习方法对大型amazon数据集进行极化，得到了满意的准确率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Sentiment analysis on large scale Amazon product reviews

The world we see nowadays is becoming more digitalized. In this digitalized world e-commerce is taking the ascendancy by making products available within the reach of customers where the customer doesn't have to go out of their house. As now a day's people are relying on online products so the importance of a review is going higher. For selecting a product, a customer needs to go through thousands of reviews to understand a product. But in this prospering day of machine learning, going through thousands of reviews would be much easier if a model is used to polarize those reviews and learn from it. We used supervised learning method on a large scale amazon dataset to polarize it and get satisfactory accuracy.

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2018 IEEE International Conference on Innovative Research and Development (ICIRD)

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