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About Movie Recommender System Using K-Means Clustering AND K-Nearest Neighbor
This document proposes a movie recommender system using K-Means clustering and K-Nearest Neighbor algorithms. It takes the Movielens dataset from Kaggle. The system is implemented in Python. It uses K-Means clustering to group similar movies together and KNN to find movies most similar to a user's preferences based on ratings. The proposed system is shown to have a lower RMSE than existing techniques, indicating it provides better recommendations.
Detailed Information
| Author: | ['Armin Shahab'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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