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New Technology of Library and Information Service  2015, Vol. 31 Issue (11): 26-32    DOI: 10.11925/infotech.1003-3513.2015.11.05
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Study on the Modified Method of Feature Weighting with Complex Networks
Du Kun, Liu Huailiang, Guo Lujie
School of Economics & Management, Xidian University, Xi'an 710126, China
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[Objective] This paper aims to calculate feature weights more accurately for the improvement of the accuracy of text similarity calculation. [Methods] The semantic association among features is considered to structure text complex networks and select features. An improved calculation method of feature weighting is proposed to carry out the Chinese text classification experiment with the definition of category correlation coefficient and the combination of the feature selection results. [Results] Experiment results show that the proposed Chinese text classification method works better in classification than the TFIDF algorithm. [Limitations] The parameters in the feature selection evaluation function need to be given. [Conclusions] Compared with the traditional TFIDF algorithm, the new algorithm is more accurate in the representation of feature weights.

Received: 26 May 2015      Published: 06 April 2016
:  TP391  

Cite this article:

Du Kun, Liu Huailiang, Guo Lujie. Study on the Modified Method of Feature Weighting with Complex Networks. New Technology of Library and Information Service, 2015, 31(11): 26-32.

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