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A Way to Detect the Opinion Sentences from Short Texts by the Vote-AdaBoost Combining Classify Method

机译:一种方法可以通过Clote-Adaboost组合分类方法检测短文本的意见句子

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Because of the sparse sentiment features of network short texts, the identify result of common classification methods which are efficacious in texts with tradition structures are unsatisfactory. This article tries to combine multiple classifiers combination and integrated learning methods to solve this problem. Vote-AdaBoost combining classify method is constructed to optimize the appropriate classifier as the voting combination in iterative learning process. Finally, an effective classification method to detect the opinion sentences of short texts is obtained, and the effectiveness of this method is verified by experiments.
机译:由于网络短文本的稀疏情绪特征,识别常见分类方法的结果,这些方法在具有传统结构的文本中有效的效果是不令人满意的。本文试图结合多个分类器组合和集成学习方法来解决此问题。 CloT-Adaboost组合分类方法被构造成优化适当的分类器作为迭代学习过程中的投票组合。最后,获得了检测短文本意见句的有效分类方法,通过实验验证了该方法的有效性。

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