| dc.contributor | 資管系 | |
| dc.creator (作者) | 簡士鎰 | |
| dc.creator (作者) | Chien, Shihyi | |
| dc.creator (作者) | Hsu, Chan;Tsao, Ching-Chih;Weng, Yu-Liang;Tang, Cheng-Yi;Chang, Yu-Wen;Kang, Yihuang | |
| dc.date (日期) | 2022-03 | |
| dc.date.accessioned | 7-十月-2022 13:44:23 (UTC+8) | - |
| dc.date.available | 7-十月-2022 13:44:23 (UTC+8) | - |
| dc.date.issued (上傳時間) | 7-十月-2022 13:44:23 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/142357 | - |
| dc.description.abstract (摘要) | The present study collects a large amount of HRI-related research studies and analyzes the research trends from 2010 to 2021. Through the topic modeling technique, our developed ML model is able to retrieve the dominant research factors. The preliminary results reveal five important topics, handover, privacy, robot tutor, skin de deformation, and trust. Our results show the research in the HRI domain can be divided into two general directions, namely technical and human aspects regarding the use of robotic applications. At this point, we are increasing the research pool to collect more research studies and advance our ML model to strengthen the robustness of the results. | |
| dc.format.extent | 110 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | HRI `22: Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction, pp. 812-815 | |
| dc.title (題名) | A Machine Learning Approach to Model HRI Research Trends in 2010~2021 | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.5555/3523760.3523882 | |
