Cover Image

Music Recommender System Using Machine Learning Content-Based Filtering Technique

The constant advancement of web development trends and technology has resulted in a big number of web systems that are frequently visited on a regular basis. Among the web systems that have been established, there are systems that allow users to listen to music online without having to download it t...

Full description

Saved in:
Bibliographic Details
Main Author: Foong, Kin Hong
Format: Undergraduates Project Papers
Language:English
Published: 2022
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/40550/1/CB19053.pdf
http://umpir.ump.edu.my/id/eprint/40550/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.40550
record_format eprints
spelling my.ump.umpir.405502024-02-29T07:03:50Z http://umpir.ump.edu.my/id/eprint/40550/ Music Recommender System Using Machine Learning Content-Based Filtering Technique Foong, Kin Hong QA75 Electronic computers. Computer science QA76 Computer software The constant advancement of web development trends and technology has resulted in a big number of web systems that are frequently visited on a regular basis. Among the web systems that have been established, there are systems that allow users to listen to music online without having to download it to their devices. With the increasing popularity of music streaming, music recommender systems are important instruments for increasing digital music consumption. Machine Learning is a form of Artificial Intelligence that will make systems to think like human being. Machine Learning allows a system to learn gradually to improve its accuracy in predicting future outcome. The objective of this project is to develop a music recommendation system using one of the Machine Learning techniques which is content-based filtering technique. The aim of this study is to study about music recommender system on how it is implemented and to design and develop a music recommender system. In this study, methods of K-Mean Clustering, Euclidean Distance and Cosine Similarity are implemented. These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. These algorithms identify hidden patterns or data groupings without the assistance of a human. It is the best option for exploratory data analysis because of its ability to find informational similarities and differences. Based on analysis on music user listen to during usage, the system will determine the feature values of that song. This allows the algorithm to select similar songs after calculation in database would best match the user's interests at any given time. K-Mean Clustering will cluster the data, according to the similarities of each song, separate them by different group. Cosine Similarity will calculate the cosine distance with other data and recommend the one with shorter distance. Euclidean Distance will calculate the direct distance between two vectors and recommend the one with shorter distance. 2022-05 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40550/1/CB19053.pdf Foong, Kin Hong (2022) Music Recommender System Using Machine Learning Content-Based Filtering Technique. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
QA76 Computer software
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Foong, Kin Hong
Music Recommender System Using Machine Learning Content-Based Filtering Technique
description The constant advancement of web development trends and technology has resulted in a big number of web systems that are frequently visited on a regular basis. Among the web systems that have been established, there are systems that allow users to listen to music online without having to download it to their devices. With the increasing popularity of music streaming, music recommender systems are important instruments for increasing digital music consumption. Machine Learning is a form of Artificial Intelligence that will make systems to think like human being. Machine Learning allows a system to learn gradually to improve its accuracy in predicting future outcome. The objective of this project is to develop a music recommendation system using one of the Machine Learning techniques which is content-based filtering technique. The aim of this study is to study about music recommender system on how it is implemented and to design and develop a music recommender system. In this study, methods of K-Mean Clustering, Euclidean Distance and Cosine Similarity are implemented. These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. These algorithms identify hidden patterns or data groupings without the assistance of a human. It is the best option for exploratory data analysis because of its ability to find informational similarities and differences. Based on analysis on music user listen to during usage, the system will determine the feature values of that song. This allows the algorithm to select similar songs after calculation in database would best match the user's interests at any given time. K-Mean Clustering will cluster the data, according to the similarities of each song, separate them by different group. Cosine Similarity will calculate the cosine distance with other data and recommend the one with shorter distance. Euclidean Distance will calculate the direct distance between two vectors and recommend the one with shorter distance.
format Undergraduates Project Papers
author Foong, Kin Hong
author_facet Foong, Kin Hong
author_sort Foong, Kin Hong
title Music Recommender System Using Machine Learning Content-Based Filtering Technique
title_short Music Recommender System Using Machine Learning Content-Based Filtering Technique
title_full Music Recommender System Using Machine Learning Content-Based Filtering Technique
title_fullStr Music Recommender System Using Machine Learning Content-Based Filtering Technique
title_full_unstemmed Music Recommender System Using Machine Learning Content-Based Filtering Technique
title_sort music recommender system using machine learning content-based filtering technique
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/40550/1/CB19053.pdf
http://umpir.ump.edu.my/id/eprint/40550/
_version_ 1822924171364007936
score 13.232414

Similar Items