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Authors: Meghan Patil, Sainaya Brid, Stuti Dhebar

Machine Learning

Introduction:

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…

Sainaya

Computer Engineer inclined towards Data Science

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