Knowledge-Enriched Recommendations: Bridging the Gap in Alloy Material Selection With Large Language Models
Navigating materials performance databases efficiently is a persistent challenge in materials science and engineering, particularly in the selection of alloy materials. While recommendation systems address information overload, traditional approaches relying on historical user data face limitations...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10937740/ |
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