Discovering Interdisciplinary Research Based on Neural Networks
Interdisciplinary research promotes the emergence of scientific innovation. Researchers want to find interdisciplinary research in their research field. However, the number of scientific papers published today is increasing, and completing this task by hand is time-consuming and laborious. A neural...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2022.908733/full |
| _version_ | 1828528107149066240 |
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| author | Tao He Wei Fu Jianqiao Xu Zhihong Zhang Jiuxing Zhou Ying Yin Zhenjie Xie |
| author_facet | Tao He Wei Fu Jianqiao Xu Zhihong Zhang Jiuxing Zhou Ying Yin Zhenjie Xie |
| author_sort | Tao He |
| collection | DOAJ |
| description | Interdisciplinary research promotes the emergence of scientific innovation. Researchers want to find interdisciplinary research in their research field. However, the number of scientific papers published today is increasing, and completing this task by hand is time-consuming and laborious. A neural network is a machine learning model that simulates the connection mode of neurons in the human brain. It is an important application of bionics in the artificial intelligence field. This paper proposes an approach to discovering interdisciplinary research automatically. The method generates an IRD-BERT neural network model for discovering interdisciplinary research based on the pre-trained model BERT. IRD-BERT is used to simulate the domain knowledge of experts, and author keywords can be projected into vector space by this model. According to the keyword distribution in the vector space, keywords with semantic anomalies can be identified. Papers that use these author keywords are likely to be interdisciplinary research. This method is applied to discover interdisciplinary research in the deep learning research field, and its performance is better than that of similar methods. |
| first_indexed | 2024-12-11T21:47:40Z |
| format | Article |
| id | doaj.art-23fa7500f1ef4072a356f109cfb1b0a3 |
| institution | Directory Open Access Journal |
| issn | 2296-4185 |
| language | English |
| last_indexed | 2024-12-11T21:47:40Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj.art-23fa7500f1ef4072a356f109cfb1b0a32022-12-22T00:49:33ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852022-06-011010.3389/fbioe.2022.908733908733Discovering Interdisciplinary Research Based on Neural NetworksTao HeWei FuJianqiao XuZhihong ZhangJiuxing ZhouYing YinZhenjie XieInterdisciplinary research promotes the emergence of scientific innovation. Researchers want to find interdisciplinary research in their research field. However, the number of scientific papers published today is increasing, and completing this task by hand is time-consuming and laborious. A neural network is a machine learning model that simulates the connection mode of neurons in the human brain. It is an important application of bionics in the artificial intelligence field. This paper proposes an approach to discovering interdisciplinary research automatically. The method generates an IRD-BERT neural network model for discovering interdisciplinary research based on the pre-trained model BERT. IRD-BERT is used to simulate the domain knowledge of experts, and author keywords can be projected into vector space by this model. According to the keyword distribution in the vector space, keywords with semantic anomalies can be identified. Papers that use these author keywords are likely to be interdisciplinary research. This method is applied to discover interdisciplinary research in the deep learning research field, and its performance is better than that of similar methods.https://www.frontiersin.org/articles/10.3389/fbioe.2022.908733/fullneural networkinterdisciplinary researchBERTdeep learningvector space |
| spellingShingle | Tao He Wei Fu Jianqiao Xu Zhihong Zhang Jiuxing Zhou Ying Yin Zhenjie Xie Discovering Interdisciplinary Research Based on Neural Networks Frontiers in Bioengineering and Biotechnology neural network interdisciplinary research BERT deep learning vector space |
| title | Discovering Interdisciplinary Research Based on Neural Networks |
| title_full | Discovering Interdisciplinary Research Based on Neural Networks |
| title_fullStr | Discovering Interdisciplinary Research Based on Neural Networks |
| title_full_unstemmed | Discovering Interdisciplinary Research Based on Neural Networks |
| title_short | Discovering Interdisciplinary Research Based on Neural Networks |
| title_sort | discovering interdisciplinary research based on neural networks |
| topic | neural network interdisciplinary research BERT deep learning vector space |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2022.908733/full |
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