Concept
Improved Concept Embeddings for Learning Prerequisite Chains: Methods
- Poincaré embeddings (Nickel and Kiela, 2017) is a method that better fit for data with latent hierarchies than other embedding models using the Euclidean vector space.
- Dhingra et al. (2018) introduced a method to obtain Poincaré word embeddings from natural language text.
- This paper combines the two methods above to obtain prerequisite relations between concepts from two datasets in the domain of Natural Language Processing.
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Updated 2020-07-29
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Data Science
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Improved Concept Embeddings for Learning Prerequisite Chains: Datasets
Improved Concept Embeddings for Learning Prerequisite Chains: Poincaré embeddings
Improved Concept Embeddings for Learning Prerequisite Chains: Generating Poincaré embeddings from natural-language text corpora
Improved Concept Embeddings for Learning Prerequisite Chains: Model parameters
Improved Concept Embeddings for Learning Prerequisite Chains: Evaluation methods