Abstract
The development of Knowledge Graphs (KGs) significantly relies on the advancements in Named Entity Recognition (NER), which is often hindered by the limited availability of specialised, labelled datasets. Geoscience researchers are exploring innovative strategies for NER due to the lack of a robust labelled terms corpus. In this work, the efficacy of NER in the automatic generation of KGs is examined, and opportunities for further research are identified.
| Original language | English |
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| Title of host publication | 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024 |
| Place of Publication | Wellington |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| ISBN (Electronic) | 9798350389678 |
| ISBN (Print) | 9798350389685 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS) - Wellington, Wellington, New Zealand Duration: 8 Apr 2024 → 10 Apr 2024 |
Publication series
| Name | 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024 |
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Conference
| Conference | International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS) |
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| Country/Territory | New Zealand |
| City | Wellington |
| Period | 8/04/24 → 10/04/24 |
Bibliographical note
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