yumeng5/WeSTClass
[CIKM 2018] Weakly-Supervised Neural Text Classification
This project helps classify large collections of text documents into categories, even when you only have a few examples or descriptions for each category. You provide either class names, a few keywords per class, or a small set of pre-labeled documents. The system then outputs predicted category labels for all your unclassified documents. This is useful for researchers, data scientists, or analysts who need to organize vast amounts of text data with minimal manual labeling.
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Use this if you need to automatically categorize a large corpus of text documents but have very limited manually labeled examples.
Not ideal if you have a substantial amount of manually labeled data available for training, as this tool is specifically designed for weak supervision scenarios.
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78
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29
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 06, 2018
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