Abstract
Text classification is an important research direction of text mining and the research of Chinese text automatic classification is also becoming a research focus of intelligent classification. Against the particularity of the Chinese text classification, this paper presents a three-dimensional vector space model on the basis of the vector space model to improve the accuracy and efficiency of text classification. Experimental results show that the accuracy rate increased to 98.8125% which proves that the algorithm is effective.
| Original language | English |
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| Title of host publication | Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012 |
| Pages | 1324-1327 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 2012 International Conference on Computer Science and Service System, CSSS 2012 - Nanjing, China Duration: 11 Aug 2012 → 13 Aug 2012 |
Publication series
| Name | Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012 |
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Conference
| Conference | 2012 International Conference on Computer Science and Service System, CSSS 2012 |
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| Country/Territory | China |
| City | Nanjing |
| Period | 11/08/12 → 13/08/12 |
Keywords
- SVM
- feature vector
- field dictionary
- statistical methods
- text classificaiton
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Zhang, J., Wang, Q., Li, Y., Li, D., & Hao, Y. (2012). A method for chinese text classification based on three-dimensional vector space model. In Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012 (pp. 1324-1327). Article 6394572 (Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012). https://doi.org/10.1109/CSSS.2012.334