Classifier construction method and device as well as Chinese text sentiment classification method and system
A construction method and classifier technology, which is applied in the direction of instruments, special data processing applications, electrical digital data processing, etc., can solve the problems of high dependence on application fields and long construction time of classifiers, so as to avoid labor costs and shorten construction Time, the effect of improving the accuracy rate
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[0068] Example 1: I don't like this product.
[0069] In the sentence of example 1, if the emotional word is "like" and the negative keyword "no" appears in the sentence, the emotional polarity of the emotional word "like" is changed, that is, the emotional polarity of "like" is changed from positive turn negative.
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[0070] Example 2: I like the idea of this product, but the quality is not acceptable to me.
[0071] In the sentence of Example 2, if the emotional word is "like", and the transition keyword "but" appears in the next sentence of the sentence it is in, the emotional polarity of the emotional word "like" is changed, that is, the emotion of "like" The polarity changes from positive to negative.
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[0072] Example 3: It would be nice if the color was red.
[0073] In the sentence of Example 3, if the emotional word is "good", and in the sentence where it is located, the keyword "if" appears in front of the emotional word "good", then the emotional polarity of the emotional word "good" is changed. , that is, to change the emotional polarity of "good" from positive to negative.
[0074] In yet another embodiment of the present invention, step S106 may include: if the difference between the number of emotional words with positive emotional polarity and the number of emotional words with negative emotional polarity is greater than a set threshold, determining the sample to be labeled The sentiment polarity of is positive; if the difference between the number of sentiment words with negative sentiment polarity and the number of sentiment words with positive sentiment polarity is greater than the set threshold, the sentiment polarity of the sample to be marked is determined to ...
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