Knowledge-Enriched Recommendations: Bridging the Gap in Alloy Material Selection With Large Language Models

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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Bibliographic Details
Main Authors: Tongwei Wu, Shiyu Du, Yiming Zhang, Honggang Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Recommender systems
knowledge graph
large language models
data augmentation
Online Access:https://ieeexplore.ieee.org/document/10937740/
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https://ieeexplore.ieee.org/document/10937740/

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