/Music-Recommendation-System-using-KNN

CSE541-Machine-Learning-2022-GANJedis

Music Recommendation System

Introduction

The number of hours an average person spends on listening to music, be it while working or studying or during one’s leisure time, is substantially increasing day by day. With the increase of user base on applications like spotify, it often becomes difficult to discover new music that matches one’s interests. So, the main aim of the project here is to identify the best solutions for music recommendation.

The Problem Statement

To use K Nearest Neighbors to provide the user with recommendation of songs based on what the user has been listening to in the past. This is a supervised learning problem where the input will be the previous songs and the output will be the recommended songs. This will be a personalized user experience differing from user to user.

Uses in real life

1. To provide better recommendation of songs to the users based on the previously top heard songs of the user.

References

1. https://pandas.pydata.org/ https://scikit-learn.org/stable/
2. https://kaggle.com
3. https://towardsdatascience.com/prototyping-a-recommender-system-step-by-step-part-1-knn-item-based-collaborative-filtering-637969614ea
4. https://www.frontiersin.org/articles/10.3389/fams.2019.00044/full
5. https://www.researchgate.net/publication/336162555_A_Music_Recommendation_System_Based_on_logistic_regression_and_eXtreme_Gradient_Boosting
6. https://silo.tips/download/project-report-cs-240a-applied-parallel-computing-k-nearest-neighborhood-based-m
  1. https://www.kaggle.com/datasets/mrmorj/dataset-of-songs-in-spotify
  2. https://deepnote.com/@zi-xiao-li/Spotify-fd3c414d-44ef-42d2-b9f4-51d7faf159c7
  3. https://www.kaggle.com/code/richardcsuwandi/spotify-time-series-analysis/notebook
  4. A Deep Temporal Neural Music Recommendation Model Utilizing Music and User Metadata Hai-Tao Zheng 1,* , Jin-Yuan Chen 1 , Nan Liang 1 , Arun Kumar Sangaiah 2 , Yong Jiang 1 and Cong-Zhi Zhao 3
  5. Liao, K., 2018. Prototyping a Recommender System Step by Step Part 1: KNN Item-Based Collaborative Filtering. [online] Medium. Available at: https://towardsdatascience.com/prototyping-a-recommender-system-step-by-step-part-1-knn-item-based-collaborative-filtering-637969614ea [Accessed 20 March 2022].
  6. M. Schedl, “Deep Learning in Music Recommendation Systems,” Frontiers, 01-Jan-1AD. [Online]. Available: https://www.frontiersin.org/articles/10.3389/fams.2019.00044/full. [Accessed: 28-Mar-2022].
  7. “A music recommendation system based on logistic regression ...” [Online]. Available: https://www.researchgate.net/publication/336162555 A Music Recommendation System Based on logistic regression and eXtreme Gradient Boosting. [Accessed: 28-Mar-2022].



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