IBMWatson推荐系统_HTML_Jupyter Notebook_下载.zip

# 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](https://recommendation-eng.herokuapp.com/) - [App Code (Heroku)](https://github.com/mkucz95/recommendation_engine/tree/app/app) - Collaborative Filtering - Rank based recommendations - Content based recommendations (user's read articles, or certain specified articles) - dataset visualisation