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- W4205654027 abstract "With the explosion of internet information, people feel helpless and difficult to choose in the face of massive information. However, the traditional method to organize a huge set of original documents is not only time-consuming and laborious, but also not ideal. The automatic text classification can liberate users from the tedious document processing work, recognize and distinguish different document contents more conveniently, make a large number of complicated documents institutionalized and systematized, and greatly improve the utilization rate of information. This paper adopts termed-based model to extract the features in web semantics to represent document. The extracted web semantics features are used to learn a reduced support vector machine. The experimental results show that the proposed method can correctly identify most of the writing styles." @default.
- W4205654027 created "2022-01-26" @default.
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- W4205654027 date "2022-07-14" @default.
- W4205654027 modified "2023-10-01" @default.
- W4205654027 title "English Article Style Recognition and Matching by Using Web Semantics" @default.
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- W4205654027 doi "https://doi.org/10.4018/ijmcmc.293751" @default.
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