Sentiment analysis or opinion mining aims to determine attitudes, judgments and opinions of customers for a product or a service. This is a great system to help manufacturers or servicers know the satisfaction level of customers about their products or services. From that, they can have appropriate adjustments. We use a popular machine learning method, being Support Vector Machine, combine with the library in Waikato Environment for Knowledge Analysis (WEKA) to build Java web program which analyzes the sentiment of English comments belongs one in four types of woman products. That are dresses, handbags, shoes and rings. We have developed and test our system with a training set having 300 comments and a test set having 400 comments. The experimental results of the system about precision, recall and F measures for positive comments are 89.3%, 95.0% and 92,.1%; for negative comments are 97.1%, 78.5% and 86.8%; and for neutral comments are 76.7%, 86.2% and 81.2%.
翻译:感官分析或意见挖掘旨在确定某种产品或服务客户的态度、判断和意见。 这是一个帮助制造商或服务商了解客户对其产品或服务的满意度的伟大系统。 从这个系统,他们可以进行适当的调整。 我们使用一种流行的机器学习方法,即支持矢量机,与Waikato环境知识分析图书馆(WEKA)合作,建立爪哇网络程序,该程序分析英语评论的情绪属于四种女性产品中的一种,即服装、手袋、鞋和环。我们开发和测试了我们的系统,培训了300条评论,测试了400条评论。系统关于精确度、回顾和F措施的实验结果为89.3%、95.0%和92.1%;负面评论为97.1%、78.5%和86.8%;中性评论为76.7%、86.2%和81.2%。