Music Recommendation System Using Machine Learning

Author:

Varsha Verma 1,Ninad Marathe 1,Parth Sanghavi 1,Dr. Prashant Nitnaware 1

Affiliation:

1. Department of Information Technology, PCE, Navi Mumbai, Maharashtra, India

Abstract

In our project, we will be using a sample data set of songs to find correlations between users and songs so that a new song will be recommended to them based on their previous history. We will implement this project using libraries like NumPy, Pandas.We will also be using Cosine similarity along with CountVectorizer. Along with this,a front end with flask that will show us the recommended songs when a specific song is processed.

Publisher

Technoscience Academy

Subject

General Medicine

Reference10 articles.

1. Luo Zhenghua, “Realization of Individualized Recommendation System on Books Sale,” IEEE 2012 International Conference on Management of e-Commerce and e-Government. pp.10-13.

2. Tewari, A.S. Kumar, and Barman, A.G, “Book recommendation system based on combining features of content-based filtering, collaborative filtering and association rule mining,” International Advance Computing Conference (IACC), IEEE, pp 500 – 503, April 2014.

3. Robin Burke, “Hybrid Recommender Systems: Survey and Experiments”, California State University, Department of Information Systems and Decision Sciences, Vol. 12, No. 4, pp. 331-370, March 2012.

4. Anil Poriya, Neev Patel, Tanvi Bhagat, and RekhaSharma, “Non-Personalized Recommender SystemsandUser-basedCollaborative Recommender Systems”, International Journal of Applied Information Systems (IJAIS), FCS, Vol. 6, No. 9, March 2014.

5. Fang, J., Grunberg, D., Luit, S., & Wang, Y. (2017, December). Development of a music recommendation system for motivating exercise. In Orange Technologies (ICOT), 2017 International Conference on (pp. 83-86). IEEE.

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