Semantic conceptual primitives computing in text classification

This paper presents a method for enhancing text classification performance with semantic computing. It adopts conceptual primitives with semantic relations as knowledge expression. Based on the semantic expression, it mined the association relation of primitives among different text classification,...

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Bibliographic Details
Published in2014 International Conference on Asian Language Processing (IALP) pp. 215 - 218
Main Authors Quan Zhang, Yi Yuan, Xiangfeng Wei, Zhejie Chi, Peimin Cong, Yihua Du
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
association of concepts
association rule
Association rules
Computational modeling
Feature extraction
primitives of concepts
semantic computing
Semantics
Support vector machines
Text categorization
text classification
Training
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Summary:This paper presents a method for enhancing text classification performance with semantic computing. It adopts conceptual primitives with semantic relations as knowledge expression. Based on the semantic expression, it mined the association relation of primitives among different text classification, and these association rules take association relation as text classification feature. The presented method not only considers what kind of the semantic primitives that a text contains, but also takes account of the association relation of the semantic primitives. Moreover, we test the method with public text classification text set. The experiment result shows that, comparing with the commonly used methods, this method prompts text classification performance.
DOI:10.1109/IALP.2014.6973472