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Interdisciplinary Subject Recognition Based on Feature Measurement and PhraseLDA Model——Case Study of Nanotechnology in Agricultural Environment |
Zhang Zhenqing,Sun Wei() |
Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, Beijing 100081, China |
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Abstract [Objective] This paper aims to identify the interdisciplinary subjects based on the feature measure method and the PhraseLDA model. [Methods] First, we analyzed the subjects’ interdisciplinary characteristics and constructed their measurement index system. Then, we identified the interdisciplinary subjects with the help of the PhraseLDA model. Finally, we conducted an empirical study of nanotechnology applications in agricultural environments. [Results] A total of 24 cross-topic were objectively identified, including catalyst preparation, soil bioremediation, and many more. Compared with the traditional identification method, the cross-topic recognition rate of the proposed method increased by 71.40%, and the recognition rate of fine-grained topics increased by 42.86%. [Limitations] The number of topics and interdisciplinary topic identification indicators of the PhraseLDA topic model were decided after repeating calculation and debugging. Therefore, the proposed method depends on the rationality of the relevant thresholds. [Conclusions] The proposed method can effectively identify interdisciplinary topics and support scientific decision-making and technological innovation research in related fields.
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Received: 24 June 2022
Published: 07 September 2023
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Fund:Supporting Task of the Ministry of Agriculture and Rural Affairs(JBYW-AII-2022-18);2022 Scientific and Technological Innovation Project Task of Agricultural Information Institute, Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2016-AII);National Social Science Fund of China(18CTQ028) |
Corresponding Authors:
Sun Wei,ORCID:0000-0002-6419-0953,E-mail: sunwei@caas.cn。
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