yuzhimanhua/MetaCat
Minimally Supervised Categorization of Text with Metadata (SIGIR'20)
This tool helps organize large collections of text documents, like product reviews or social media posts, into predefined categories. You provide your documents along with any relevant associated information (like author, tags, or product IDs), and it automatically assigns a category to each document, even if you only have a few examples for each category. It's designed for data analysts, content managers, or researchers who need to classify text using minimal labeled data.
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Use this if you have a substantial collection of text documents and associated metadata that you need to categorize, but only have a small number of hand-labeled examples for each category.
Not ideal if you have no metadata accompanying your text documents or if you require a fully unsupervised clustering approach.
Stars
47
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 02, 2024
Commits (30d)
0
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