基于自然语言处理的商品评论智能化分析网站
An Intelligent Analysis Website for Product Reviews Based on Natural Language Processing

随着互联网技术的迅速发展，网上购物已成为人们日常生活中不可或缺的一部分。消费者往往希望通过其他人对商品的真实评论分析来判断商品的质量和是否值得购买。本文针对这一问题，通过Django和pyechart等搭建了评论情感分析和模型训练可视化网站。网站使用了两种情感分析模型(GRU模型和LSTM模型)对评论中所蕴含的情感倾向及特征进行了分析。模型通过Python网络爬虫技术获取大量商品评论，对这些评论进行数据预处理和Word2Vec词向量化后进行训练，旨在提高模型训练的准确度。网站用户通过简单的操作就可以实现商品的搜索、可视化分析、模型的自定义训练和使用。本文情感分析网站有助于消费者更好地了解商品质量，也为企业改进产品提供了重要依据。
With the rapid development of internet technology, online shopping has become an indispensable part of people’s daily lives. Consumers often wish to judge the quality and worth of a product based on authentic reviews from others. This article addresses this issue by building a sentiment analysis and model training visualization website using Django and pyechart. The site employs two sentiment analysis models (GRU and LSTM models) to analyze the emotional tendencies and characteristics contained in the reviews. The models use Python web scraping techniques to collect a large number of product reviews, which are then preprocessed and vectorized using Word2Vec for training, aiming to enhance the accuracy of model training. Users of the website can easily search for products, perform visual analysis, and customize and utilize the training of models. This sentiment analysis website helps consumers better understand product quality and also provides an important basis for enterprises to improve their products.