Publication
Relationship Extraction with Weakly Supervised Learning Based on Process-Structure-Property-Performance Reciprocity
MDR Open
We developed a computer aided material design system that extracts relationships from natural language texts in weakly labeled data. We believe that our study makes a significant contribution to the literature because we trained a machine learning model with minimal annotated relation data to extract relationships between scientific concepts from scientific articles.
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Relation extraction with weakly supervised learning based on process structure property performance reciprocity.pdf | 1.46 MB | MDR Open |
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