Authors: Meghan Patil, Sainaya Brid, Stuti Dhebar
A recommendation system is based on two filtering methods:
· Content Filtering — creates a profile for each user or product to characterize its nature (Success Case: Music Genome Project)
· Collaborative Filtering — analyses relationships between users and inter-dependencies among products to identify new user-item associations (Success Case: Tapestry). Generally, more accurate then content filtering however, it suffers from cold start problem.
Cold start problem: If new user exist sand does not have any inter-dependencies among others, we can’t recommend anything
Collaborative filtering has two methods:
· Neighborhood Method — computing the…
Computer Engineer inclined towards Data Science