An investigation of neural information retrieval based temporal embeddings and knowledge extraction for scientific insight generation
Humans today generate information at an unprecedented rate, leading to a vast accumulation of knowledge. This immense amount of data poses challenges in extracting both explicit information and implicit knowledge, predicting scientific events, and investigating scientific trends and trajectories. Fo...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2025
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| Online Access: | https://eprints.nottingham.ac.uk/78905/ |