| dc.contributor | 圖檔所 | |
| dc.creator (作者) | 陳志銘 | |
| dc.creator (作者) | Liang, Chien-Yun;Li, Ming-Chaun;Chen, Chih-Ming;Lin, Chun-Yu | |
| dc.date (日期) | 2024-07 | |
| dc.date.accessioned | 26-Dec-2024 11:26:05 (UTC+8) | - |
| dc.date.available | 26-Dec-2024 11:26:05 (UTC+8) | - |
| dc.date.issued (上傳時間) | 26-Dec-2024 11:26:05 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/154814 | - |
| dc.description.abstract (摘要) | To support digital humanities research more effectively and efficiently, this study develops a novel Knowledge Graph Analysis Tool of People and Organizations (KGAT-PO) for the Digital Humanities Research Platform for Biographies of Chinese Malaysian Personalities (DHRP-BCMP) based on artificial intelligence (AI) technology. This tool would not only allow humanities scholars to look at the relationships between people but also has the potential for aiding digital humanities research by identifying latent relationships between people via relationships between people and organizations. To verify the effectiveness of KGAT-PO, a counterbalanced design was applied to compare research participants in two groups using DHRP-BCMP with and without KGAT-PO, respectively, to perform people relationship inquiry and to see if there were significant differences in the effectiveness of exploring relationships between people. The results show that the DHRP-BCMP with KGAT-PO could help research participants improve the effectiveness of exploring relationships between people. | |
| dc.format.extent | 112 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | The 18th International Conference on E-Service and Knowledge Management, International Institute of Applied Informatics | |
| dc.title (題名) | Exploring Relationships Between People and Organizations: A Digital Humanities Research Tool Based on AI Technology for Knowledge Graph Analysis | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1109/IIAI-AAI63651.2024.00016 | |
| dc.doi.uri (DOI) | https://doi.org/10.1109/IIAI-AAI63651.2024.00016 | |
