Emotion classifying method fusing intrinsic feature and shallow feature
A technology of emotion classification and deep features, applied in the field of emotion classification, can solve problems such as ignoring semantic relations, achieve the effect of improving classification performance and increasing accuracy
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[0025] The present invention will be further explained below in conjunction with the drawings:
[0026] Such as figure 1 As shown, the specific steps of the emotion classification method that combines deep and shallow features of the present invention are:
[0027] Step 1: Collect sentiment text corpus from the Internet, and manually mark the categories. For example, the text label of positive emotion is 1 and the text label of negative emotion is 2. And remove the space at the beginning and end of the text, and express the data in the text as a sentence, which is convenient for subsequent processing. And the corpus is divided into training set and test set. The training set is used to train the emotion classification model, and the test set is used to test the effect of the model classification.
[0028] Step 2: First collect sentiment dictionaries from the Internet. The sentiment dictionary is a basic resource for text sentiment analysis, which is actually a collection of sentime...
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