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Topic Modeling on Biomedical Literature

Topic modelingPubMedLDAT-SNE
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Jun 13, 2018 8:28 AM
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This workflow shows a topic modeling approach using documents related to user-selected diseases of interest. It starts, after selecting disease names, with the extraction of text documents from the database PubMed and performs topic modeling using the Latent Dirichlet Allocation (LDA) method. Additionally, two interactive views will created using components. Data sources used in this workflow:

External resources

  • PubMed
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.6.3
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

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    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime
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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Statistics Nodes (Labs)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime
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    KNIME TextprocessingTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime

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