Non Personalized recommender System
This program generates a list of top 5 movies that occur with a list of movie list.
We're using two formulas; a simple one and one advanced one which does not suffer
from majority bias.
1. Simple: (X and Y) / X
2: Advanced: ((X and Y) / X) / ((!X and Y) / !X)
A Recommender System using Content based filtering
Here we use TF-IDF concept to build a prototype of content based recommender system.
The user profile calculation happens in two ways. Look into comments for more info.
User-User Collaborative filtering based Recommendation system.
This user user collaborative filtering based recommender system computes user similarity
and for each item's score calculate the most similar users. Later we normalize it to generate
the recommendation for a user.
Evaluation of various recommendation algorithms and implementing emtropy metrics
item-item collaborative filtering based recommender system.
Singular value decomposition based recommendation system.