qkrdmsghk/TextSSL
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
This project helps machine learning researchers working with document classification. It takes text documents and learns an underlying sparse structure to improve how well a model can categorize them, even for new, unseen documents. The output is a more robust and accurate document classification model, particularly for academic or industry researchers exploring advanced natural language processing techniques.
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Use this if you are an academic researcher or an NLP engineer developing cutting-edge document classification systems and need to improve model performance on unseen data.
Not ideal if you are looking for an out-of-the-box solution for general document classification tasks without a deep understanding of graph neural networks or sparse structure learning.
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32
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11
Language
Python
License
MIT
Category
Last pushed
Nov 25, 2024
Commits (30d)
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