Earthquake event knowledge graph construction and reasoning
Efficient decision-making in earthquake emergencies plays a crucial role in ensuring individual safety, protecting personal property, and maintaining societal stability. However, traditional approaches to earthquake emergency decision-making rely on manual analysis or rule-based methods, which often...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2383768 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850246991090548736 |
|---|---|
| author | Peiyuan Qiu Linke Pang Yong Luo Yaohui Liu Huaqiao Xing Kang Liu Guoliang Zhuang |
| author_facet | Peiyuan Qiu Linke Pang Yong Luo Yaohui Liu Huaqiao Xing Kang Liu Guoliang Zhuang |
| author_sort | Peiyuan Qiu |
| collection | DOAJ |
| description | Efficient decision-making in earthquake emergencies plays a crucial role in ensuring individual safety, protecting personal property, and maintaining societal stability. However, traditional approaches to earthquake emergency decision-making rely on manual analysis or rule-based methods, which often struggle to fully leverage the wealth of information and uncover hidden data connections. Consequently, the efficiency of earthquake emergency decision-making is compromised. To address this issue, this study proposes a method for constructing an earthquake event knowledge graph and utilizing it for decision-making in earthquake emergencies. Firstly, specialized earthquake event knowledge ontology is developed, tailored to the unique characteristics of earthquake event data. Secondly, structured instances of earthquake event knowledge are extracted from text using transfer learning techniques, enabling the construction of the earthquake event knowledge graph. Thirdly, the earthquake event knowledge is represented as multidimensional vectors using knowledge graph representation learning technology. This facilitates the identification of similar earthquake events through inference based on vector similarity computation. In conclusion, the results of a case-based study demonstrate the effectiveness of the proposed method in providing accurate outcomes, facilitating earthquake event matching, enabling the retrieval and reuse of historical earthquake event knowledge, and serving as a valuable reference for earthquake emergency decision-making. |
| format | Article |
| id | doaj-art-4a601112f26b4d1a96a788e1de2e772e |
| institution | OA Journals |
| issn | 1947-5705 1947-5713 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj-art-4a601112f26b4d1a96a788e1de2e772e2025-08-20T01:59:04ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132024-12-0115110.1080/19475705.2024.2383768Earthquake event knowledge graph construction and reasoningPeiyuan Qiu0Linke Pang1Yong Luo2Yaohui Liu3Huaqiao Xing4Kang Liu5Guoliang Zhuang6School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, ChinaEarthquake Administration of Shanxi Province, Taiyuan, Shanxi, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, ChinaShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangzhou, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, ChinaEfficient decision-making in earthquake emergencies plays a crucial role in ensuring individual safety, protecting personal property, and maintaining societal stability. However, traditional approaches to earthquake emergency decision-making rely on manual analysis or rule-based methods, which often struggle to fully leverage the wealth of information and uncover hidden data connections. Consequently, the efficiency of earthquake emergency decision-making is compromised. To address this issue, this study proposes a method for constructing an earthquake event knowledge graph and utilizing it for decision-making in earthquake emergencies. Firstly, specialized earthquake event knowledge ontology is developed, tailored to the unique characteristics of earthquake event data. Secondly, structured instances of earthquake event knowledge are extracted from text using transfer learning techniques, enabling the construction of the earthquake event knowledge graph. Thirdly, the earthquake event knowledge is represented as multidimensional vectors using knowledge graph representation learning technology. This facilitates the identification of similar earthquake events through inference based on vector similarity computation. In conclusion, the results of a case-based study demonstrate the effectiveness of the proposed method in providing accurate outcomes, facilitating earthquake event matching, enabling the retrieval and reuse of historical earthquake event knowledge, and serving as a valuable reference for earthquake emergency decision-making.https://www.tandfonline.com/doi/10.1080/19475705.2024.2383768Earthquakeknowledge graphemergency decision-makingsimilarity reasoningdeep learning |
| spellingShingle | Peiyuan Qiu Linke Pang Yong Luo Yaohui Liu Huaqiao Xing Kang Liu Guoliang Zhuang Earthquake event knowledge graph construction and reasoning Geomatics, Natural Hazards & Risk Earthquake knowledge graph emergency decision-making similarity reasoning deep learning |
| title | Earthquake event knowledge graph construction and reasoning |
| title_full | Earthquake event knowledge graph construction and reasoning |
| title_fullStr | Earthquake event knowledge graph construction and reasoning |
| title_full_unstemmed | Earthquake event knowledge graph construction and reasoning |
| title_short | Earthquake event knowledge graph construction and reasoning |
| title_sort | earthquake event knowledge graph construction and reasoning |
| topic | Earthquake knowledge graph emergency decision-making similarity reasoning deep learning |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2024.2383768 |
| work_keys_str_mv | AT peiyuanqiu earthquakeeventknowledgegraphconstructionandreasoning AT linkepang earthquakeeventknowledgegraphconstructionandreasoning AT yongluo earthquakeeventknowledgegraphconstructionandreasoning AT yaohuiliu earthquakeeventknowledgegraphconstructionandreasoning AT huaqiaoxing earthquakeeventknowledgegraphconstructionandreasoning AT kangliu earthquakeeventknowledgegraphconstructionandreasoning AT guoliangzhuang earthquakeeventknowledgegraphconstructionandreasoning |