A collaborative product recommendation engine that uses data from an e-commerce store to make similar product suggestions based on the selected item. This is performed through community detection using Louvain clustering. A Flask API has been used to create the user interface and Gephi visualisations have been included to analyse the detected communities.
A product recommendation engine is essentially a software that records an user’s actions on e-commerce websites and analyses the data obtained to make
product suggestions that might interest the user. This can enhance the customer experience and even boost sales of the e-commerce website that makes use of it.
Community detection can be used to identify products that are most likely to be bought together thereby facilitating a product recommendation engine.
Here communities will be formed on the basis of the information obtained from user purchase patterns.
- You can see the detected communities here.
- Python3
- Flask
- Gephi
- Gephi Visualisation: https://ritika-07.github.io/Product-Recommendation-Engine/network/#
- Dataset: https://archive.ics.uci.edu/ml/datasets/Online+Retail#