hadryan / musicrecommendationsystem-4

MusicRecommendationSystem

• Create a music recommendation system
• Given a dataset of users, write code to find the Nearest Neighbor recommendations for user X based on Euclidean similarity measure
• Find artists that other users in the data set have rated to recommend artists that user X may also like
• Personlaize recommendations Utility Matrix - Model

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• Utility Function u: X * I -> R
• X = set of Customers
• I = Set of Items
• R = set of ratings
• R is a totally ordered set
• e.g., 0-5 Stars, real number [0,1]

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Key Problems

1. Gathering "known" ratings for the matrix

• How to collect the data in the utility matrix

2. Extrapolate unknown ratings from the known ones

• Mainly interested in high unknown ratings
• We are not interested in knowing what you don't like but what you do like

3. Evaluating extrapolation methods

• How to measure success/performance of recommendation methods