Data for: Concept Embedding to Measure Semantic Relatedness for Biomedical Information Ontologies

Published: 22 Apr 2019 | Version 1 | DOI: 10.17632/nbb2ntpdw5.1
Contributor(s):
  • Junseok Park,
    Unspecified
    Korea Advanced Institute of Science and Technology
    First Author
  • Kwangmin Kim,
    Kwangmin Kim
    Korea Advanced Institute of Science and Technology
    Second Author
  • Doheon Lee,
    Computer Science
    Korea Advanced Institute of Science and Technology
    Corresponding Author
  • Woochang Hwang
    Biochemistry, Genetics and Molecular Biology
    University of Cambridge
    Third Author

Description of this data

we extended the definition information of the CUI terms using the Wikipedia database to improve the coverage of the similarity model. Second, we adopted document embedding for vector representations of the CUI terms. We used UMLS2015AB for the data.

Experiment data files

This data is associated with the following publication:

Concept embedding to measure semantic relatedness for biomedical information ontologies

Published in: Journal of Biomedical Informatics

Latest version

  • Version 1

    2019-04-22

    Published: 2019-04-22

    DOI: 10.17632/nbb2ntpdw5.1

    Cite this dataset

    Park, Junseok; Kim, Kwangmin; Lee, Doheon; Hwang, Woochang (2019), “Data for: Concept Embedding to Measure Semantic Relatedness for Biomedical Information Ontologies”, Mendeley Data, v1 http://dx.doi.org/10.17632/nbb2ntpdw5.1

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Categories

Document Analysis, Similarity Measure, Biomedical Research

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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