Research Areas
Biography and Research Information
OverviewAI-generated summary
Mohammed Corresp is a graduate student at the University of Arkansas at Fayetteville. His research focuses on the application of machine learning techniques to enhance consumer health vocabularies. Specifically, he has worked on developing an automated method that utilizes GloVe word embeddings and an auxiliary lexical resource to enrich these vocabularies. This work aims to improve the accessibility and usability of health information for consumers. Corresp has one publication, co-authored with Susan Gauch, which details this automated enrichment method.
Metrics
- Publications: 1
Selected Publications
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Peer Review #1 of "An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource (v0.1)" (2021)
Collaboration Network
Top Collaborators
- Peer Review #1 of "An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource (v0.1)"
- Peer Review #1 of "An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource (v0.1)"
- Peer Review #1 of "An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource (v0.1)"
- Peer Review #1 of "An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource (v0.1)"
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