Abstract
At present, the studies in foreign on natural language processing for automated essay scoring are in full swing. However, these studies are aimed at native English speakers, and it is essentially different from the focus on domestic CET essay scoring. With large-scale popularization of the CET automated essay scoring by the Ministry of Education, the problem on essay scoring is becoming the bottleneck of improving efficiency and large-scale popularization. In this paper, from the perspective of data mining, using classification algorithm KNN-based-association, essay is evaluated in both content and language way. Compared with manual scoring, we analyze their difference.
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Jiang, H., Huang, G., Liu, J. (2011). The Research on CET Automated Essay Scoring Based on Data Mining. In: Zhou, M., Tan, H. (eds) Advances in Computer Science and Education Applications. Communications in Computer and Information Science, vol 202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22456-0_15
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DOI: https://doi.org/10.1007/978-3-642-22456-0_15
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