dheeraj7596/META
Code for the paper "META: Metadata-Empowered Weak Supervision for Text Classification"
This project helps researchers and data analysts to categorize large collections of text documents, like books or articles, more accurately by incorporating additional details beyond just the text itself. It takes your text data, along with seed words for each category and information about associated metadata (like authors or timestamps), and outputs an improved text classifier. This is ideal for anyone who needs to automatically sort and understand large volumes of textual information.
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Use this if you need to classify text documents and have access to related metadata that could help distinguish between categories, such as authors, publication venues, or timestamps.
Not ideal if your text classification task relies solely on the text content and no additional metadata is available or relevant.
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Python
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Last pushed
Apr 13, 2021
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