This Web-Application was created to demonstrate and analyse the graph theory based recommender model (https://github.com/05kashyap/SocialNet_RecSys).
It has been hosted at: https://kashyap05.pythonanywhere.com/
Project Report:
| Evaluation Metrics | Result |
|---|---|
| Accuracy | 0.7877 |
| Precision (at k=5) | 1.0 |
| Recall (at k=5) | 0.538095 |
| F1 Score | 0.6996 |
| Graph Matching Metrics | Result |
|---|---|
| GED | 0.6 |
| Edge overlap ratio | 0.91044 |
| Recall (at k=5) | 0.538095 |
| Structural Hammering Distance | 0.19999 |
Setup Instructions(To run the application locally): (Ideally inside a virtual env)
- Clone the repository
git clone [https://github.com/05kashyap/GDSC_meme_feed](https://github.com/05kashyap/GraphLink.git)- Install requirements.txt
pip install -r requirements.txt
- Make migrations
python3 manage.py makemigrations
- Apply migrations
python3 manage.py migrate
- Apply migrations
python3 manage.py runserver