TinusChen / Text-Clustering-API

Implementation of a text clustering algorithm using Kmeans clustering in order to derive quick insights from unstructured text

Text-Clustering-API

Implementation of a text clustering algorithm using Kmeans clustering in order to derive quick insights from unstructured text. Please check the below links for details -

• https://machinelearningblogs.com/2017/01/26/text-clustering-get-quick-insights-from-unstructured-data/
• https://machinelearningblogs.com/2017/01/26/text-clustering-get-quick-insights-from-unstructured-data/

Docker Setup

0. Install Docker
1. Run git clone https://github.com/vivekkalyanarangan30/Text-Clustering-API
2. Open docker terminal and navigate to /path/to/Text-Clustering-API
3. Run docker build -t clustering-api .
4. Run `docker run -p 8180:8180 clustering-api
5. Access http://192.168.99.100:8180/apidocs/index.html brom your browser

Native Setup

1. Anaconda distribution of python 2.7
2. pip install -r requirements.txt
3. Some dependencies from nltk (nltk.download() from python console and download averaged perceptron tagger)

Run it

1. Place the script in any folder
2. Open command prompt and navigate to that folder
3. Type "python CLAAS.py"and hit enter
4. Go over to http://localhost:8180/apidocs/index.html in your browser (preferably Chrome) and start using.