 Löffel, E. P. (2019) generated prerequisite relations between concepts in the domain of Natural Language Processing from two datasets, TutorialBank and LectureBank, by representing natural language text corpora as Poincaré embedding.

Improved Concept Embeddings for Learning Prerequisite Chains

Li, I., etc.(2019) introduced a new dataset, LectureBank, in 5 different domains with 208 manually-labeled prerequisite relation topics, and evaluated four binary classifiers and two Graph Convolutional Networks (GCNs) models in predicting prerequisite relationship.

What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning

- Löffel, E. P. (2019). Improved Concept Embeddings for Learning Prerequisite Chains.
- Li, I., Fabbri, A. R., Tung, R. R., & Radev, D. R. (2019, July). What should i learn first: Introducing lecturebank for nlp education and prerequisite chain learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 6674-6681).

University of Michigan - Ann Arbor

- Identification and prediction of the prerequisite relationship 

Learn Before

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