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

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.