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| Chinese Named Entity Disambiguation Based on Multivariate Similarity Fusion |
Shi Shuiqian,Jin Jing,Shen Gengyu,Wang Baojia,Ren Ni( ) |
| Institute of Agricultural Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China |
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Abstract [Objective] This paper aims to solve the ambiguity problems arising from mapping multiple entities of the same name with different meanings to a knowledge base. It improves the accuracy of entity disambiguation. [Methods] We proposed a multi-dimensional similarity fusion method. It utilizes the semantic similarity of entity context, the entity attributes' background similarity, and the topic words' semantic similarity to characterize entities. [Results] We examined the new model on the agricultural dataset from Wikipedia. The proposed method achieved an accuracy of 89.7%, outperforming traditional methods. [Limitations] The proposed method is only applicable in specific fields. [Conclusions] The new method addresses the entity disambiguation issues in specific fields. It can be applied to a broader range of entity disambiguation scenarios.
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Received: 12 November 2022
Published: 28 April 2023
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| Fund:National Social Science Fund of China(19BTQ032) |
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Corresponding Authors:
Ren Ni，ORCID： 0000-0002-3789-7347，E-mail：rn@jaas.ac.cn。
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