A Study on Clustering of the Online-Handwriting of Uyghur Based on Improved K-Neighbor Classifier

Ling Wang; I. Dawa; Guo Ping Su; Slam Wshour

doi:10.4028/www.scientific.net/AMR.846-847.1115

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847A Study on Clustering of the Online-Handwriting of...

A Study on Clustering of the Online-Handwriting of Uyghur Based on Improved K-Neighbor Classifier

Abstract:

Online-handwriting of Uyghur word categorization (UWC) based on improved K-NN is studied in this paper. Firstly, features are selected by correlation analysis method (CAM), and correlation is measured by linear correlation coefficient (LCC). Secondly, K-NN algorithm is improved and classifier is established. Finally, the classifier is applied in UWC. The experiment results show that the method has good performance on online handwriting of UWC.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1115-1119

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1115

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Online since:

November 2013

Authors:

Ling Wang*, I. Dawa, Guo Ping Su, Slam Wshour

Keywords:

Handwriting, K-Neighbor Classifier, Uyghur

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* - Corresponding Author

References

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