dborrelli/chat-intents
Clustering sentence embeddings to extract message intent
This tool helps you automatically organize customer support messages, survey responses, or any collection of short text into meaningful groups. You provide the text messages, and it identifies common themes or 'intents' within them, giving you a summary of each group and labeling every message. It's designed for anyone managing customer feedback, user research data, or large volumes of text conversations to quickly understand key topics.
174 stars. No commits in the last 6 months.
Use this if you have a large dataset of short text messages and need to automatically identify the main topics or intentions expressed within them without manually reading through each one.
Not ideal if you have very long, complex documents or if you already know the exact categories you want to sort your messages into.
Stars
174
Forks
25
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 19, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/dborrelli/chat-intents"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
sz128/slot_filling_and_intent_detection_of_SLU
slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s...
yuanxiaosc/BERT-for-Sequence-Labeling-and-Text-Classification
This is the template code to use BERT for sequence lableing and text classification, in order to...
asappresearch/dialog-intent-induction
Code and data for paper "Dialog Intent Induction with Deep Multi-View Clustering", Hugh Perkins...
hellohaptik/HINT3
This repository contains datasets and code for the paper "HINT3: Raising the bar for Intent...
taishan1994/pytorch_bert_intent_classification_and_slot_filling
基于pytorch的中文意图识别和槽位填充