Using Semantic Correlation of HowNet for Short Text Classification

Ya Hui Ning; Li Zhang; Ya Rong Ju; Wei Jia Wang; Shun Qin Li

doi:10.4028/www.scientific.net/AMM.513-517.1931

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Using Semantic Correlation of HowNet for Short...

Using Semantic Correlation of HowNet for Short Text Classification

Abstract:

A method using the HowNet ontologies for short texts classification was proposed. First, the domain high frequency words were got as the feature words. Then the feature words were extended to concept by HowNet, which extended the feature from semantic and amends the feature scarcity. Last, the word semantic correlation values were got by calculating the distance between different concepts in node tree. Experimental results prove that the classification efficiency and precision are both improved.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

1931-1934

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.1931

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Online since:

February 2014

Authors:

Ya Hui Ning*, Li Zhang, Ya Rong Ju, Wei Jia Wang, Shun Qin Li

Keywords:

HowNet, Ontology, Semantic, Short-Text, Text Classification

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* - Corresponding Author

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