Chinese Text Classification with a KNN Classifier Using an Adjusted Feature Weighting Method

Wei Ran Lin; Zhi Hui Wu; Li Chao Feng; Wai Bin Huang

doi:10.4028/www.scientific.net/AMM.50-51.700

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 50-51Chinese Text Classification with a KNN Classifier...

Chinese Text Classification with a KNN Classifier Using an Adjusted Feature Weighting Method

Abstract:

KNN algorithm is used for Chinese text classification in this paper. First, TF-IDF is chosen as the feature weighting method. To the characteristics of corpus used in this paper, TF-IDF is adjusted to a new method. At last, experimental result shows the accuracy of KNN text classifier can be improved with the adjusted feature weighting method.

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Periodical:

Applied Mechanics and Materials (Volumes 50-51)

Pages:

700-703

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.50-51.700

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Online since:

February 2011

Authors:

Wei Ran Lin, Zhi Hui Wu, Li Chao Feng, Wai Bin Huang

Keywords:

Feature Weight, KNN, Text Classification

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References

[1] Songbo Tan: An effective refinement strategy for KNN text classifier. Expert Systems with Applications Vol. 30-2(2006), pp.290-298.

DOI: 10.1016/j.eswa.2005.07.019

Google Scholar

[2] Yu-Long Qiao , Jeng-Shyang Pan , Sheng-He Sun : Improved K nearest neighbor classification algorithm. Circuits and Systems Vol. 2(2005), pp.1101-1104.

DOI: 10.1109/apccas.2004.1413076

Google Scholar

[3] Huang Wei, Liu Yi , Gao Bing , Yang Ke-wei. Study on Method of Word Segmentation in Feature Selection in Chinese Text Categorization, Proceedings of Third International Conference on Knowledge Discovery and Data Mining, (2010).

DOI: 10.1109/wkdd.2010.61

Google Scholar

[4] Jung-Yi Jiang , Shie-Jue Lee . A Weight-based Feature Extraction Approach for Text Classification, Proceedings of Second International Conference on Innovative Computing, Information and Control, (2007).

DOI: 10.1109/icicic.2007.109

Google Scholar

[5] Jain, A., Zongker, D.: Feature selection: evaluation, application, and small sample performance. Pattern Analysis and Machine Intelligence Vol. 19-2(1997), pp.153-158.

DOI: 10.1109/34.574797

Google Scholar

[6] Yanling Li , Jing Yuan , Xia Ye : Method for feature word weight calculating, Proceedings of IEEE International Conference on Intelligent Computing and Intelligent Systems, (2009).

DOI: 10.1109/icicisys.2009.5357840

Google Scholar

[7] Information on http: /www. searchforum. org. cn/tansongbo/corpus-senti. htm.

Google Scholar