CHAI Mingke, LI Dongmei, ZHUANG Tingting, YANG Shuyi. Named Entity Disambiguation Based on Classified and Structural Semantic Relatedness[J]. Chinese Journal of Electronics, 2018, 27(6): 1176-1182. doi: 10.1049/cje.2018.08.008
Citation: CHAI Mingke, LI Dongmei, ZHUANG Tingting, YANG Shuyi. Named Entity Disambiguation Based on Classified and Structural Semantic Relatedness[J]. Chinese Journal of Electronics, 2018, 27(6): 1176-1182. doi: 10.1049/cje.2018.08.008

Named Entity Disambiguation Based on Classified and Structural Semantic Relatedness

doi: 10.1049/cje.2018.08.008
Funds:  This work is supported by the National Natural Science Foundation of China (No.61772078), the Fundamental Research Funds for the Central Universities (No.TD2014-02), and Beijing Undergraduate Training Programs for Innovation and Entrepreneurship (No.201610022063).
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  • Corresponding author: LI Dongmei (corresponding author) was born in 1972. She received the Ph.D. degree from Beijing Jiaotong University in 2014. Now she is an associate professor at School of Information Science and Technology, Beijing Forestry University. Her research interests include natural language processing, knowledge engineering and semantic web. (Email:lidongmei@bjfu.edu.cn)
  • Received Date: 2018-01-22
  • Rev Recd Date: 2018-03-02
  • Publish Date: 2018-11-10
  • Named entity disambiguation is presented to solve the problem of name ambiguity. Traditional disambiguation methods merely use the word frequency to calculate the weights of attributes, yet ignore the important information from low frequency words. We propose a named entity disambiguation method based on classified and structural semantic relatedness. Structural semantic relatedness is computed by capturing the explicit semantic relatedness and the implicit structural semantic knowledge. Classified semantic relatedness is computed by main attributes which can determine the domain entity identity. The experimental results show our method can significantly improve the disambiguation performance and achieve 90.5% accuracy of disambiguation.
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