kptopic 0.0.4

A short description of my package

KPTopic

• No more Topic Modeling
• No need Training
• No more Machine Learning but Human-like Reading
• Get the Insights of Text Big and Small

KPTopic: a graph-based approach to represent perception (text in general) by key parts of speech. KPTopic solved the coherence crux that current topic modeling algorithms are trying to deal with but failed. KPTopic extracts the topics from text corpus syntactically, semantically and pragmatically instead of a meaningless combination of words from topic modeling.

Key Parts: Noun, Adjective, Verb and Emoji

KPTopic Vs Topic Modeling results from the following text:

“Thai food was great we loved it. Thiland also has beautiful beach resorts, we will come to Thailand again👍”

• KPTopic Result

• Topic Modeling Result

['food','thailand','resort','great','love', 'beautiful']

Installation

if need coreferee: 
 pip install kptopic[coreferee_spacy] 
 #!pip install kptopic[crosslingual-coreference_spacy] # a alternative coreference package 
 python3 -m coreferee install en 
 python -m spacy download en_core_web_lg 

else:
 pip install spacy 
 pip install kptopic  
 python -m spacy download en_core_web_lg

Getting Started

For an in-depth overview of the features of KPTopic you can check the Documents or you can follow along with one of the examples as follows:

Name	Link
KPTopic Quick Start
KPTopic with Real Example
KPTopic VS Topic Modelling
KPTopic Network Comparison

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" !!!"""

• 2 Keyparts Wordclouds

The following wordclouds are generated from a real example of corpus comprised of reviews by those who visit Thailand.

• 3 Community and Gray Perceptual Unit Networks

Citation

To cite the KPTopic paper, please use the following bibtex reference:

@article{pengyang,
  title={KPTopic},
  author={Peng, Yang},
  journal={a1},
  year={202}
}