Optimizing an EduKG pipeline with local Wikipedia dumps, better text extraction, disambiguation, and pruning lifts accuracy from 0.40 to 0.47 and cuts processing time by 10-100x.
In: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
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An Optimized Pipeline for Automatic Educational Knowledge Graph Construction
Optimizing an EduKG pipeline with local Wikipedia dumps, better text extraction, disambiguation, and pruning lifts accuracy from 0.40 to 0.47 and cuts processing time by 10-100x.