havelhakimi/LHA-HTC
Code for the paper "Label hierarchy alignment for improved hierarchical text classification" acepted in 2023 IEEE Bigdata
This project helps researchers and data scientists categorize text documents into predefined hierarchical structures more accurately. It takes raw text data and a known label hierarchy as input, then outputs the classified documents with improved accuracy by aligning the labels within that hierarchy. This is designed for anyone working with large volumes of text that need to be organized into complex, multi-level categories.
No commits in the last 6 months.
Use this if you need to classify documents into a nested, tree-like category system and want to improve the accuracy of those classifications.
Not ideal if your text classification problem involves flat, non-hierarchical categories or if you don't have a predefined label hierarchy.
Stars
14
Forks
—
Language
Python
License
—
Category
Last pushed
Mar 18, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/havelhakimi/LHA-HTC"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kk7nc/HDLTex
HDLTex: Hierarchical Deep Learning for Text Classification
richliao/textClassifier
Text classifier for Hierarchical Attention Networks for Document Classification
RandolphVI/Hierarchical-Multi-Label-Text-Classification
The code of CIKM'19 paper《Hierarchical Multi-label Text Classification: An Attention-based...
yumeng5/LOTClass
[EMNLP 2020] Text Classification Using Label Names Only: A Language Model Self-Training Approach
sgrvinod/a-PyTorch-Tutorial-to-Text-Classification
Hierarchical Attention Networks | a PyTorch Tutorial to Text Classification