RETRACTED: Optimization of Data Mining and Analysis System for Chinese Language Teaching Based on Convolutional Neural Network (Retracted Article)
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作者:
Chen, Xi
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机构:
Northeast Normal Univ, Dept Literature, Changchun 130024, Peoples R China
Changchun Educ Collage, Changchun 130033, Peoples R ChinaNortheast Normal Univ, Dept Literature, Changchun 130024, Peoples R China
Chen, Xi
[1
,2
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机构:
[1] Northeast Normal Univ, Dept Literature, Changchun 130024, Peoples R China
[2] Changchun Educ Collage, Changchun 130033, Peoples R China
Chinese language is also an important way to understand Chinese culture and an important carrier to inherit and carry forward Chinese traditional culture. Chinese language teaching is an important way to inherit and develop Chinese language. Therefore, in the era of big data, data mining and analysis of Chinese language teaching can effectively sum up experience and draw lessons, so as to improve the quality of Chinese language teaching and promote Chinese language culture. Text clustering technology can analyze and process the text information data and divide the text information data with the same characteristics into the same category. Based on big data, combined with convolutional neural network and K-means algorithm, this paper proposes a text clustering method based on convolutional neural network (CNN), constructs a Chinese language teaching data mining analysis system, and optimizes it so that the system can better mine Chinese character data in Chinese language teaching data in depth and comprehensively. The results show that the optimized k-means algorithm needs 683 iterations to achieve the target accuracy. The average K-measure value of the optimized system is 0.770, which is higher than that of the original system. The results also show that K-means algorithm can significantly improve the clustering effect, optimize the data mining analysis system of Chinese language teaching, and deeply mine the Chinese data in Chinese language teaching, so as to improve the quality of Chinese language teaching.
机构:
Harbin Normal Univ, Sch Econ, Harbin 150025, Heilongjiang, Peoples R ChinaHarbin Normal Univ, Sch Econ, Harbin 150025, Heilongjiang, Peoples R China
机构:
Yunnan Univ, Kunming 650091, Yunnan, Peoples R China
Southwest Forestry Univ, Kunming 650224, Yunnan, Peoples R ChinaYunnan Univ, Kunming 650091, Yunnan, Peoples R China
Zhao, Yili
Xu, Dan
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机构:
Yunnan Univ, Kunming 650091, Yunnan, Peoples R ChinaYunnan Univ, Kunming 650091, Yunnan, Peoples R China
Xu, Dan
Zhang, Yan
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h-index: 0
机构:
Southwest Forestry Univ, Kunming 650224, Yunnan, Peoples R ChinaYunnan Univ, Kunming 650091, Yunnan, Peoples R China
Zhang, Yan
ADVANCES IN IMAGE AND GRAPHICS TECHNOLOGIES, IGTA 2016,
2016,
634
: 238
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244
机构:
Anshan Normal Coll, Dept Management, Anshan 114005, Liaoning, Peoples R ChinaAnshan Normal Coll, Dept Management, Anshan 114005, Liaoning, Peoples R China
机构:
Changchun Sci Tech Univ, Fac Linguist & Cultural Studies, Changchun 130600, Jilin, Peoples R ChinaChangchun Sci Tech Univ, Fac Linguist & Cultural Studies, Changchun 130600, Jilin, Peoples R China
机构:
Huanggang Normal Univ, Dept Comp Sch, Huanggang 438000, Hubei, Peoples R ChinaHuanggang Normal Univ, Dept Comp Sch, Huanggang 438000, Hubei, Peoples R China
Zhou, Jing
Liu, Quanju
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h-index: 0
机构:
Huanggang Normal Univ, Dept Comp Sch, Huanggang 438000, Hubei, Peoples R ChinaHuanggang Normal Univ, Dept Comp Sch, Huanggang 438000, Hubei, Peoples R China