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- W3043420616 abstract "With the rapid development and application of the electric power Internet of Things, the number of electronic texts in the system has increased dramatically. However, due to inadequate system management and the complexity of information sources, the current electronic text management in power grid systems has the problems of disordered format, redundant information, and unclear classification. Aiming at these problems, this paper designs and constructs a power grid text classification model based on Word2vec and SF-HAN. The model uses the CBoW model in Word2vec to generate word vectors, and then uses the improved SF-HAN network to predict and classify the extracted word vectors. The accuracy of the method is verified by experiments." @default.
- W3043420616 created "2020-07-23" @default.
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- W3043420616 date "2020-06-01" @default.
- W3043420616 modified "2023-09-23" @default.
- W3043420616 title "Text classification model based on Word2vec and SF-HAN" @default.
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- W3043420616 doi "https://doi.org/10.1109/itoec49072.2020.9141865" @default.
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