Irvinglove/char-CNN-text-classification-tensorflow
the implement of text understanding from scratch
This project helps classify news articles into categories directly from their raw text. You feed in the text of news articles, and it outputs predictions about what category each article belongs to (e.g., sports, politics, business). It's designed for anyone needing to automatically sort or organize large collections of text, particularly news content, without needing pre-processed data.
No commits in the last 6 months.
Use this if you need to categorize news articles or similar short texts efficiently and automatically, learning directly from the raw characters rather than relying on word-based features.
Not ideal if your text data is highly structured, requires deep semantic understanding beyond basic categorization, or you're working with languages that don't benefit from character-level analysis.
Stars
35
Forks
35
Language
Python
License
—
Category
Last pushed
Jul 21, 2017
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Irvinglove/char-CNN-text-classification-tensorflow"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
carpedm20/lstm-char-cnn-tensorflow
in progress
ilivans/tf-rnn-attention
Tensorflow implementation of attention mechanism for text classification tasks.
ahmedbesbes/character-based-cnn
Implementation of character based convolutional neural network
AlexGidiotis/Document-Classifier-LSTM
A bidirectional LSTM with attention for multiclass/multilabel text classification.
NonvolatileMemory/AAAI_2019_EXAM
Official implementation of "Explicit Interaction Model towards Text Classification"