Tang, Ruipeng and Yang, Jianbu and Tang, Jianxun and Aridas, Narendra Kumar and Abu Talip, Mohamad Sofian (2024) Design of agricultural question answering information extraction method based on improved BILSTM algorithm. Scientific Reports, 14 (1). p. 24444. ISSN 2045-2322, DOI https://doi.org/10.1038/s41598-024-70534-z.
Full text not available from this repository.Abstract
With the rapid growth of the agricultural information and the need for data analysis, how to accurately extract useful information from massive data has become an urgent first step in agricultural data mining and application. In this study, an agricultural question-answering information extraction method based on the BE-BILSTM (Improved Bidirectional Long Short-Term Memory) algorithm is designed. Firstly, it uses Python's Scrapy crawler framework to obtain the information of soil types, crop diseases and pests, and agricultural trade information, and remove abnormal values. Secondly, the information extraction converts the semi-structured data by using entity extraction methods. Thirdly, the BERT (Bidirectional Encoder Representations from Transformers) algorithm is introduced to improve the performance of the BILSTM algorithm. After comparing with the BERT-CRF (Conditional Random Field) and BILSTM algorithm, the result shows that the BE-BILSTM algorithm has better information extraction performance than the other two algorithms. This study improves the accuracy of the agricultural information recommendation system from the perspective of information extraction. Compared with other work that is done from the perspective of recommendation algorithm optimization, it is more innovative; it helps to understand the semantics and contextual relationships in agricultural question and answer, which improves the accuracy of agricultural information recommendation systems. By gaining a deeper understanding of farmers' needs and interests, the system can better recommend relevant and practical information.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Information extraction; Question and answer system; Natural language processing; Knowledge graph; Agricultural information recommendation |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering Faculty of Languages and Linguistics |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 17 Feb 2025 02:59 |
| Last Modified: | 17 Feb 2025 02:59 |
| URI: | http://eprints.um.edu.my/id/eprint/47419 |
Actions (login required)
 |
View Item |
