Metadata-Version: 2.1
Name: keypartx
Version: 0.1.6
Summary: A Graph-based Perception(Text) Representation
Home-page: 
Author: Peng Yang
Author-email: pyseptimo@outlook.com
License: MIT
Keywords: text representation,text mining,nlp,topic modeling,emoji,image,perception
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Education
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
Provides-Extra: coreferee_spacy
License-File: LICENCE.txt


KeypartX: a graph-based approach to represent perception (text in general) by key parts of speech.

## Installation

```bash
if need coreferee: 
 pip install keypartx[coreferee_spacy] 
 python3 -m coreferee install en 
 python -m spacy download en_core_web_lg 

else:
 pip install spacy 
 pip install keypartx  
 python -m spacy download en_core_web_lg
```


## Getting Started
For an in-depth overview of the features of KeypartX
you can check the [**Documents**](https://mr./) or you can follow along 
with one of the examples as follows:

| Name  | Link  |
|---|---|
| KepartX Quick Start  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1VdKIJtMMcYRnXsne87azY7B1FXp9FpD1?usp=sharing)  |
| KepartX Sentence NLP | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1hjAU-_RP7GGzMm6rnpdJZR7LSY0KS81E?usp=sharing) |
| KepartX VS Topic Modelling |  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/14XvylCMBZ2oUnjpZhnf_658paVdvAhp0?usp=sharing) |
| KepartX Network Comparison |  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1vTx9LwIGXt5so5IdOr4zsqrgSm4sHnYe?usp=sharing)  |

## Visualization Examples 
* 1 NLP Target  

Original sentence: Thai food was great,delicousr and not expensive, we loved it. We visited 3 beach resorts, they are higly recommened... We had "Fire-Vodka" !!!

<img src="https://github.com/pengKiina/KeypartX/raw/main/images/nlp_target.png" width="70%" height="35%" align="center" />


* 2 Community and Gray Perceptual Unit Networks 

<img src="https://github.com/pengKiina/KeypartX/blob/main/images/community_gray.gif" width="70%" height="45%" align="center" />

## Citation
To cite the [KeypartX paper](https://arxiv.org/abs/2209.11844), please use the following bibtex reference:

```bibtext
@article{pengyang2022keypartx,
  title={KeypartX: Graph-based Perception (Text) Representation},
  author={Peng, Yang},
  journal={arXiv preprint arXiv:2209.11844},
  year={2022}
}
```
