摘要
挖掘旅游海量评论信息,智能分析用户情感,从而改进旅游产品和服务,是旅游电子商务成功的关键。论文从旅游网络评论信息出发,研究微博情感词汇本体的构建和基于贝叶斯分类算法的情感分类,实现了一个基于本体的旅游网络评论情感分析和预警系统。系统不仅节省了大量人力和物力,而且对制定合理的旅游政策具有一定的参考价值。
Pigging tourism information and opinion,analyzing intelligently user emotion,to improve tourism products and services are the key to the success of tourism e-commerce.This paper embarks from the tourism network review information,how to build the microblogging emotional vocabulary ontology and how to classify emotion based on Naive Bayes classification algorithm are researched,a tourism network comments sentiment analysis and early warning system is implemented based on ontology.It not only saves a large amount of manpower and material resources,but also has certain reference value to establish reasonable tourism policy.
出处
《计算机与数字工程》
2016年第4期649-652,共4页
Computer & Digital Engineering
基金
湖北省教育厅科学技术研究计划指导性项目:基于Ontology的微博话题识别及倾向性研究(编号:B2015360)资助
关键词
本体
贝叶斯分类
情感分析
预警
ontology
Naive Bayes classifier
sentiment analysis
pre-warning