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English Article Style Recognition and Matching by Using Web Semantics

English Article Style Recognition and Matching by Using Web Semantics

Mi Zhou, Lina Peng
Copyright: © 2022 |Volume: 13 |Issue: 2 |Pages: 13
ISSN: 1937-9412|EISSN: 1937-9404|EISBN13: 9781683180456|DOI: 10.4018/IJMCMC.293751
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MLA

Zhou, Mi, and Lina Peng. "English Article Style Recognition and Matching by Using Web Semantics." IJMCMC vol.13, no.2 2022: pp.1-13. http://doi.org/10.4018/IJMCMC.293751

APA

Zhou, M. & Peng, L. (2022). English Article Style Recognition and Matching by Using Web Semantics. International Journal of Mobile Computing and Multimedia Communications (IJMCMC), 13(2), 1-13. http://doi.org/10.4018/IJMCMC.293751

Chicago

Zhou, Mi, and Lina Peng. "English Article Style Recognition and Matching by Using Web Semantics," International Journal of Mobile Computing and Multimedia Communications (IJMCMC) 13, no.2: 1-13. http://doi.org/10.4018/IJMCMC.293751

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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.