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Mobile User Emotion Perception based on Weight Loss Mechanism and Support Vector Machine

机译:基于减肥机制和支持向量机的移动用户情感感知

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摘要

The implementation of mobile users' emotional perception is complex and inefficient at present. Therefore, we propose a method that realizes emotion analysis by exploring the relationship between user emotion and time characteristics, using natural language processing, SVM, and mathematical analysis methods. Then combined the corpus built by ourselves, and the CHI feature extraction method is used to extract the feature from the training data set, the data is transformed into the feature matrix according to the feature values, and the training set is modeled and trained by the SVM method, and then optimize the parameters using genetic algorithm. According to the result of the SVM decision function, the weighted idea is used to weight the data, and its weight is modeled and calculated according to the weight loss mechanism we proposed, and the final result will be obtained as a condition for the determination of emotion perception.
机译:当前,移动用户情感感知的实现复杂且效率低下。因此,我们提出了一种利用自然语言处理,SVM和数学分析方法,通过探索用户情绪与时间特征之间的关系来实现情绪分析的方法。然后结合自己构建的语料库,采用CHI特征提取方法从训练数据集中提取特征,根据特征值将数据转换为特征矩阵,并通过训练对模型进行建模和训练SVM方法,然后使用遗传算法优化参数。根据支持向量机决策函数的结果,采用加权思想对数据进行加权,并根据我们提出的失重机制对权重进行建模和计算,得出最终结果作为确定权重的条件。情绪感知。

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