Item type |
文献 / Documents(1) |
公開日 |
2021-09-30 |
アクセス権 |
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アクセス権 |
open access |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
出版社版DOI |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1109/ACCESS.2019.2930641 |
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言語 |
ja |
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関連名称 |
10.1109/ACCESS.2019.2930641 |
出版タイプ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
タイトル |
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タイトル |
Drug-Drug Interaction Extraction Based on Transfer Weight Matrix and Memory Network |
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言語 |
en |
タイトル別表記 |
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その他のタイトル |
DDI Extraction Based on Transfer Weight Matrix and Memory Network |
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言語 |
en |
著者 |
Liu, Juan
Huang, Zhong
任, 福継
Hua, Lei
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抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Extracting drug-drug interaction (DDI) in the text is the process of identifying how two target drugs in a given sentence interact. Previous methods, which were limited to conventional machine learning techniques, we are susceptible to issues such as “vocabulary gap” and unattainable automation processes in feature extraction. Inspired by deep learning in natural language preprocessing, we addressed the aforementioned problems based on dynamic transfer matrix and memory networks. A TM-RNN method is proposed by adding the transfer weight matrix in multilayer bidirectional LSTM to improve robustness and introduce a memory network for feature fusion. We evaluated the TM-RNN model on the DDIExtraction 2013 Task. The proposed model achieved an overall F-score of 72.43, which outperforms the latest methods based on support vector machine and other neural networks. Meanwhile, the experimental results also indicated that the proposed model is more stable and less affected by negative samples. |
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言語 |
en |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Drug-drug interaction extraction |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
memory network |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
multilayer bidirectional LSTM |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
transfer weight matrix |
書誌情報 |
en : IEEE Access
巻 7,
p. 101260-101268,
発行日 2019-07-23
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収録物ID |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
21693536 |
出版者 |
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出版者 |
IEEE |
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言語 |
en |
権利情報 |
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言語 |
en |
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権利情報 |
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ |
EID |
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識別子 |
354767 |
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識別子タイプ |
URI |
言語 |
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言語 |
eng |