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SAW Classification Algorithm for Chinese Text Classification

delete2015-02-27
delete6
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OA
AI
X
Xiaoli Guo
H
Huiyu Sun
T
Tie Hua Zhou
王凌 (Ling Wang) *
Z
Zhaoyang Qu
J
Jiannan Zang
DOI:10.3390/su7032338delete
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Abstract

Abstract

En 中文
Considering the explosive growth of data, the increased amount of text data's effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words have an implied correlation between text information mining and text categorization for high-correlation matching. Experiments show that SAW classification algorithm on the premise of ensuring precision in classification, significantly improve the classification precision and recall, obviously improving the performance of information retrieval, and providing an effective means of data use in the era of big data information extraction.
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Journal

Sustainability cover
Sustainability
IF:
3.3
Papers:
10.6W
Citations:
28.4W

Organization

N
northeast electric power university
Scholars:
5.7K
Papers: 3.3K
Citations: 1
C
Chungbuk National University
Scholars:
8.5K
Papers: 8.0K
Citations: 6.4K