CristianViorelPopa/BART-TL-topic-label-generation
Implementation and helper scripts for the BART-TL model - https://www.aclweb.org/anthology/2021.eacl-main.121/
This project helps researchers and data scientists automatically generate descriptive labels for topics discovered within large collections of documents. You input a collection of text documents and a set of topics derived from them, and it outputs concise, human-readable labels for each topic. This is useful for anyone working with large text datasets who needs to understand and categorize emergent themes, such as social scientists analyzing public discourse or market researchers identifying product trends.
No commits in the last 6 months.
Use this if you need to automatically generate meaningful, novel labels for latent topics found in your textual data, rather than selecting from a predefined list.
Not ideal if you're looking for a simple, off-the-shelf application to label a few topics without any technical setup or fine-tuning.
Stars
16
Forks
6
Language
Python
License
MIT
Category
Last pushed
May 20, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/CristianViorelPopa/BART-TL-topic-label-generation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DerwenAI/pytextrank
Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
Tiiiger/bert_score
BERT score for text generation
BrikerMan/Kashgari
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for...
asyml/texar
Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. ...
yohasebe/wp2txt
A command-line tool to extract plain text from Wikipedia dumps with category and section filtering