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在线商品评论已成为对商品阐述看法的主要手段,对商品评论的情感分析研究具有学术及商业价值.研究情感分析领域若干机器学习模型,通过扩充情感词典,运用机器学习方法,设计餐饮领域网上评论情感分析模型.深入探讨朴素贝叶斯、C4.5等分类算法,利用多种性能评价方法,详细讨论不同模型的分析效果,结果表明所设计模型发挥出情感词典的有效性,更加适合于判断客户情感倾向.
Online product reviews have become the main means of exposition on commodities, and the sentiment analysis of commodity reviews has academic and commercial value.Some models of machine learning in the field of emotional analysis are researched, by extending the sentiment dictionaries and using machine learning methods, Emotion analysis model.Discussed the naive Bayes, C4.5 and other classification algorithms, using a variety of performance evaluation methods, discussed in detail the analysis of different models, the results show that the design of the model to play the effectiveness of the emotional dictionary, more suitable for judging Customer emotional tendencies.