Since the positive comments may have the non-truly satisfied comments,a method which can truly reflect the sentiment of the consumers was constructed in order to decrease the non-truly satisfied comments from the positive comments.The research oriented to the consumption sentiment shows that the consumption sentiment vocabulary should be extracted at first.According to the consumption sentimental features,consumption sentiment got classified into seven classes and twentyfive subclasses,and the three-dimensional coordinate model was established.Afterwards,Protégé was used to build a consumption sentiment ontology library so that the consumption sentiment can be automatically classified by the threedimensional coordinate vocabulary classification algorithm.Moreover,the consumption sentiment judging algorithm was applied to automatically judge consumer comments based on the completed library.Finally,compared with the positive comment ratio of Taobao,the F-measure can reach more than 95％.It can eliminate the non-truly satisfied comments from positive comments and reflect the consumer's real emotion.%针对商家好评中存在非真正满意的评价问题,构建一种能够真正反映消费者情绪状态的方法,以减少好评率中非真正满意的评价.针对消费情绪进行了研究,首先从评价中提取出消费情绪词汇,根据消费情绪的特征,将消费情绪划分为7大类,25小类,建立了三维坐标模型；其次,用Protégé来构建消费情绪本体库,根据三维坐标词汇分类算法对消费情绪词汇进行自动划分；然后,根据构建的本体库,用消费情绪判断算法来自动判断消费者的评价.最后,与淘宝的好评率进行比较,F值达到了95％以上,减少了好评中非真正满意的评价,体现了消费者的真实情绪.
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