chiennv2000/LR-GCN

Label-Representative Graph Convolutional Network for Multi-Label Text Classification

26
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Experimental

This tool helps you automatically categorize documents into multiple relevant topics, even when those topics are complex or overlapping. You provide a collection of texts and a list of possible labels, and it outputs each document tagged with all its applicable labels. It's designed for data analysts, content managers, or researchers who need to efficiently organize and understand large document sets.

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Use this if you need to assign multiple predefined categories to text documents, such as tagging news articles with all relevant subjects or classifying legal documents by different case types.

Not ideal if you need to classify documents into a single category only, or if you want to discover new, undefined topics within your text.

document-classification content-tagging information-retrieval text-analytics knowledge-management
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 12 / 25

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18

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3

Language

Python

License

Last pushed

Sep 20, 2022

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