Research on named entity recognition method of marine natural products based on attention mechanism
Marine natural product (MNP) entity property information is the basis of marine drug development, and this entity property information can be obtained from the original literature. However, the traditional methods require several manual annotations, the accuracy of the model is low and slow, and the...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Chemistry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fchem.2023.958002/full |
| _version_ | 1811169419260329984 |
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| author | Xiaodong Ma Rilei Yu Chunxiao Gao Zhiqiang Wei Zhiqiang Wei Yimin Xia Xiaowei Wang Hao Liu Hao Liu |
| author_facet | Xiaodong Ma Rilei Yu Chunxiao Gao Zhiqiang Wei Zhiqiang Wei Yimin Xia Xiaowei Wang Hao Liu Hao Liu |
| author_sort | Xiaodong Ma |
| collection | DOAJ |
| description | Marine natural product (MNP) entity property information is the basis of marine drug development, and this entity property information can be obtained from the original literature. However, the traditional methods require several manual annotations, the accuracy of the model is low and slow, and the problem of inconsistent lexical contexts cannot be solved well. In order to solve the aforementioned problems, this study proposes a named entity recognition method based on the attention mechanism, inflated convolutional neural network (IDCNN), and conditional random field (CRF), combining the attention mechanism that can use the lexicality of words to make attention-weighted mentions of the extracted features, the ability of the inflated convolutional neural network to parallelize operations and long- and short-term memory, and the excellent learning ability. A named entity recognition algorithm model is developed for the automatic recognition of entity information in the MNP domain literature. Experiments demonstrate that the proposed model can properly identify entity information from the unstructured chapter-level literature and outperform the control model in several metrics. In addition, we construct an unstructured text dataset related to MNPs from an open-source dataset, which can be used for the research and development of resource scarcity scenarios. |
| first_indexed | 2024-04-10T16:42:00Z |
| format | Article |
| id | doaj.art-4a79f87f22264c2db64afa5e6a98977f |
| institution | Directory Open Access Journal |
| issn | 2296-2646 |
| language | English |
| last_indexed | 2024-04-10T16:42:00Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemistry |
| spelling | doaj.art-4a79f87f22264c2db64afa5e6a98977f2023-02-08T05:59:05ZengFrontiers Media S.A.Frontiers in Chemistry2296-26462023-02-011110.3389/fchem.2023.958002958002Research on named entity recognition method of marine natural products based on attention mechanismXiaodong Ma0Rilei Yu1Chunxiao Gao2Zhiqiang Wei3Zhiqiang Wei4Yimin Xia5Xiaowei Wang6Hao Liu7Hao Liu8College of Computer Science and Technology, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaPilot National Laboratory for Marine Science and Technology, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Ocean University of China, Qingdao, ChinaPilot National Laboratory for Marine Science and Technology, Qingdao, ChinaMarine natural product (MNP) entity property information is the basis of marine drug development, and this entity property information can be obtained from the original literature. However, the traditional methods require several manual annotations, the accuracy of the model is low and slow, and the problem of inconsistent lexical contexts cannot be solved well. In order to solve the aforementioned problems, this study proposes a named entity recognition method based on the attention mechanism, inflated convolutional neural network (IDCNN), and conditional random field (CRF), combining the attention mechanism that can use the lexicality of words to make attention-weighted mentions of the extracted features, the ability of the inflated convolutional neural network to parallelize operations and long- and short-term memory, and the excellent learning ability. A named entity recognition algorithm model is developed for the automatic recognition of entity information in the MNP domain literature. Experiments demonstrate that the proposed model can properly identify entity information from the unstructured chapter-level literature and outperform the control model in several metrics. In addition, we construct an unstructured text dataset related to MNPs from an open-source dataset, which can be used for the research and development of resource scarcity scenarios.https://www.frontiersin.org/articles/10.3389/fchem.2023.958002/fullnamed entity recognitionmarine natural productsattention mechanisminflated convolutional neural networkconditional random field |
| spellingShingle | Xiaodong Ma Rilei Yu Chunxiao Gao Zhiqiang Wei Zhiqiang Wei Yimin Xia Xiaowei Wang Hao Liu Hao Liu Research on named entity recognition method of marine natural products based on attention mechanism Frontiers in Chemistry named entity recognition marine natural products attention mechanism inflated convolutional neural network conditional random field |
| title | Research on named entity recognition method of marine natural products based on attention mechanism |
| title_full | Research on named entity recognition method of marine natural products based on attention mechanism |
| title_fullStr | Research on named entity recognition method of marine natural products based on attention mechanism |
| title_full_unstemmed | Research on named entity recognition method of marine natural products based on attention mechanism |
| title_short | Research on named entity recognition method of marine natural products based on attention mechanism |
| title_sort | research on named entity recognition method of marine natural products based on attention mechanism |
| topic | named entity recognition marine natural products attention mechanism inflated convolutional neural network conditional random field |
| url | https://www.frontiersin.org/articles/10.3389/fchem.2023.958002/full |
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