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Content Provider | IET Digital Library |
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Author | Chai, Mingke Li, Dongmei Zhuang, Tingting Yang, Shuyi |
Abstract | 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. |
Starting Page | 1176 |
Ending Page | 1182 |
Page Count | 7 |
ISSN | 10224653 |
Volume Number | 27 |
e-ISSN | 20755597 |
Issue Number | Issue 6, Nov (2018) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/cje/27/6 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/cje.2018.08.008 |
Journal | Chinese Journal of Electronics |
Publisher Date | 2018-11-01 |
Access Restriction | Open |
Rights Holder | © Chinese Institute of Electronics |
Subject Keyword | Classified Semantic Relatedness Disambiguation Performance Document Processing Technique Domain Entity Identity Explicit Semantic Relatedness Implicit Structural Semantic Knowledge Information Network Information Retrieval Technique Knowledge Engineering Technique Low Frequency Words Name Ambiguity Named Entity Disambiguation Method Natural Language Processing Structural Semantic Relatedness Text Analysis Traditional Disambiguation Method Word Frequency |
Content Type | Text |
Resource Type | Article |
Subject | Applied Mathematics Electrical and Electronic Engineering |
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