AR_Miner

Our implementation of the text miner for app reviews. Please see the original paper AR_Miner.

Video Link : https://youtu.be/bHjNEZsD5As

Getting Started

These python packages are required to run our project

sklearn

pip install sklearn

lda

pip install lda

scipy

pip install scipy

nltk

pip install nltk

nltk.corpus

Go to your python interactive model, type:

>>>nltk.download('all')

for install the nltk corpus to import stopwords

Run the project

Make sure to git clone the entire repo into your local directory and install the required packages.

Notebook structure

The notebook is used as a demo/report for our project. We import the code into the notebook.

The main code flow of our notebook includes :

1. NLP Based Preprocessing;
2. Naive Bayes/SVM Based Filtering;
3. LDA topic clustering;
4. Ranking algorithms for importance

Dataset

There are four considered apps to try:

facebook

templerun2

swiftkey

tapfish