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• W2898041880 abstract "In recent years, with the rapid development of Internet Technology, text data is growing rapidly every day. Users need to filter out the information they need from a large amount of text. Therefore, automatic text classification technology can help users find information. In order to address problems, such as ignoring contextual semantic links and different vocabulary importance in traditional text classification techniques, this paper presents a vector representation of feature words based on the deep learning tool Word2vec, and the weight of the feature words is calculated by the improved TF-IDF algorithm. By multiplying the weight of the word and the word vector, the vector representation of the word is realized. Finally, each text is represented by accumulating all the word vectors. Thus, text classification is carried out." @default.
• W2898041880 created "2018-10-26" @default.
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• W2898041880 date "2018-08-01" @default.
• W2898041880 modified "2023-10-03" @default.
• W2898041880 title "Research of Text Classification Based on Improved TF-IDF Algorithm" @default.
• W2898041880 cites W2031838470 @default.
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• W2898041880 doi "https://doi.org/10.1109/irce.2018.8492945" @default.
• W2898041880 hasPublicationYear "2018" @default.
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