Chinese text classification method based on multi-input attention network
A text classification and attention technology, applied in text database clustering/classification, neural learning methods, biological neural network models, etc., can solve problems such as unsatisfactory, no interpretability, and incomplete utilization of language features. Achieve high reliability and high classification accuracy
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[0042] like figure 1 Shown is a schematic flow chart of the method of the method of the present invention: this multi-input attention network-based Chinese text classification method provided by the present invention includes the following steps:
[0043] S1. Obtain Chinese text data;
[0044] S2. According to the Chinese text data obtained in step S1, establish a corresponding language model; specifically, the following steps are used to establish a language model:
[0045] A. Segment the acquired Chinese text data and remove stop words;
[0046] B. the Chinese text that step A obtains is converted into corresponding pinyin text;
[0047] C. the Chinese text that step A obtains and the pinyin text that step B obtains are counted respectively, obtain Chinese text statistical data and pinyin text statistical data;
[0048] D. The Chinese text statistics and pinyin text statistics obtained in step C are trained to obtain matrix data based on word vectors;
[0049] In the spe...
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