hima888 / recommendation_engine

Recommendation System with IBM Watson

Recommendation Engine with IBM Watson

This project was concieved in collaboration with Udacity and IBM Watson

Overview

In this project I aim to create a recommendation system for the IBM Watson community. The recommendation system suggests articles for users to interact.

Features

The recommender system can make recommendations in a number of ways:

1. Collaborative Filtering

• Takes into account the similarity of users and recommends the most popular articles read by similar users

2. Rank Based Recommendations

• Recommends the highest ranked articles starting with the most highly ranked

3. Content Based Filtering

• Produces recommendations based on similarity to material the user has interacted with previously. Utilizes Natural Language Processing (NLP) methodology to analyse and rank articles by similarity.

4. SVD - Matrix Factorization Recommendations

• Utilises matrix operations to predict the ranking (or in this case the boolean interaction variable)

Usage

See Deployed Web App

• App Code (Heroku)
• Collaborative Filtering
• Rank based recommendations
• Content based recommendations (user's read articles, or certain specified articles)
• dataset visualisation