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| Automatic Classification Method Based on Multi-factor Algorithm |
Li Jiao1,Huang Yongwen1,Luo Tingting1,Zhao Ruixue1,2,Xian Guojian1,2( ) |
1Agricultural Information Institute of CAAS, Beijing 100081, China
2Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs, Beijing 100081, China |
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Abstract [Objective] This paper develops an automatic method for classification indexing, aiming to better manage massive information resources and conduct knowledge discovery. [Methods] First, we analyzed the relationship between keywords (e.g., subject terms/concepts) and classification numbers. Then, we designed a multi-factor weighted algorithm. Finally, we proposed a scheme for automatic classification indexing. [Results] We examined our method with annotated corpora of authoritative domains and standard data sets. For literature with single subject classification number, the precision, recall and F values were 84.1%, 79.8%, and 81.9% respectively. For literature with two subject classification numbers, the precision, recall and F values were 83.4%, 78.8%, and 81.0%. [Limitations] The accuracy and completeness of our method relies on high-quality corpora, and the indexing of interdisciplinary literature needs to be improved. [Conclusions] The proposed method could effectively finish the classification tasks.
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Received: 24 March 2020
Published: 04 December 2020
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Corresponding Authors:
Xian Guojian
E-mail: xianguojian@caas.cn
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