Journal of Computing Science and Engineering

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Classifying Articles in Chinese Wikipedia with Fine-Grained Named Entity Types

  • Zhou, Jie (Zhengzhou Information Science and Technology Institute) ;
  • Li, Bicheng (Zhengzhou Information Science and Technology Institute) ;
  • Tang, Yongwang (Zhengzhou Information Science and Technology Institute)
  • Received : 2013.11.01
  • Accepted : 2014.07.23
  • Published : 2014.09.30
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Abstract

Named entity classification of Wikipedia articles is a fundamental research area that can be used to automatically build large-scale corpora of named entity recognition or to support other entity processing, such as entity linking, as auxiliary tasks. This paper describes a method of classifying named entities in Chinese Wikipedia with fine-grained types. We considered multi-faceted information in Chinese Wikipedia to construct four feature sets, designed different feature selection methods for each feature, and fused different features with a vector space using different strategies. Experimental results show that the explored feature sets and their combination can effectively improve the performance of named entity classification.

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References

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