havelhakimi/TLA
Code for the paper "Modeling Text-Label Alignment for Hierarchical Text Classification" acepted in ECML PKDD 2024
This project helps classify text documents into categories that are organized hierarchically, like a tree structure. It takes raw text documents and a predefined hierarchy of labels as input. It outputs a classification of each document into the most appropriate categories within that hierarchy. This is useful for researchers, data scientists, or content managers who need to organize large collections of text data with complex, nested categories.
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Use this if you need to automatically categorize text documents into a sophisticated, multi-level classification system where labels have parent-child relationships.
Not ideal if your classification task involves flat, non-hierarchical categories or if you need to classify images or other non-textual data.
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Python
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Last pushed
Mar 25, 2025
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