基于朴素贝叶斯的旅游网情感分类研究

Emotion Classification of Tourism Websites Based on Naive Bayes

朴素贝叶斯算法在人工智能、机器学习领域有着重要地位。朴素贝叶斯算法是基于贝叶斯定理与特征条件独立假设的分类方法,根据已知条件计算未发生的事情的概率,通过参考概率作出最合适的推理。笔者主要研究数据获取技术和数据处理技术。数据获取通过设计一个爬虫程序来实现,数据处理通过Jieba分词和朴素贝叶斯算法来实现。本研究使用Eclipse开发工具开发,使用Python语言进行编程,使用朴素贝叶斯算法实现文本分类。

Naive bayes algorithm plays an important role in artificial intelligence and machine learning. Naive bayes algorithm is a classification method based on the bayes theorem and the independent assumption on feature condition. It calculates the probability of the things not yet happened according to the known conditions, and makes the most appropriate inference by reference probability. The author mainly studies data acquisition and data processing technology. Data acquisition was realized by a crawler, and data processing was performed through the Jieba segmentation and the naive bayes algorithm. In this study, eclipse was used to develop, python was used for programming, and naive bayes algorithm was used to realize text classification.