Call for Papers:Vol.11 Issue.6

Submission
Last date		 28-Dec-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Music Recommendation System Using Hybrid Approach
PaperId: :  21640
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21640
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Nekkanti Likhitha Koneru Lakshmaiah Educational Foundation
Katepalli Yaswanth Sai Kumar Koneru Lakshmaiah Educational Foundation
Nakka Venkata Durga Malleswari Koneru Lakshmaiah Educational Foundation
Kuchipudi Gayatri Koneru Lakshmaiah Educational Foundation

Abstract

Artificial Intelligence & Machine Learning
Music Recommendation, Hybrid Approach, User Engagement, K-means, Streamlet.
In the digital music era, artists and creators on platforms like Spotify seek to engage and connect with their audiences. To facilitate this interaction and promote their playlists, a novel hybrid-based recommendation system is proposed. This project presents a hybrid music recommendation system that combines content-based and collaborative filtering methods to offer personalized song recommendations to users. Leveraging the Spotify API and a rich dataset of song features, this system offers an interactive and user-centric experience for music enthusiasts. The content- based filtering component analyzes audio features of songs, including danceability, energy, acousticness, instrumentals, and more. Users can input their favorite songs, and the system generates recommendations based on the similarity of these features. Additionally, users have the flexibility to fine-tune their preferences using sliders for various audio attributes. The collaborative filtering component employs K-Means clustering to group songs with similar audio characteristics. When users provide input songs, the system calculates a user profile based on the mean audio feature values of those songs. Recommendations are then generated from the cluster that best matches this profile, ensuring contextual relevance. Integration with the Spotify API enriches the dataset with song popularity, explicitness, and additional audio features. Users can listen to recommended songs directly from the interface, enhancing their music discovery experience. This hybrid recommendation system provides a dynamic and adaptable approach to music discovery, catering to diverse user preferences. Its seamless integration of content-based and collaborative filtering techniques empowers users to explore new music while staying connected with their musical tastes.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . "Music Recommendation System Using Hybrid Approach" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 612-619
MLA Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . "Music Recommendation System Using Hybrid Approach." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 612-619.
APA Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , & Kuchipudi Gayatri . (2023). Music Recommendation System Using Hybrid Approach. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 612-619.
Chicago Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . "Music Recommendation System Using Hybrid Approach." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 612-619.
Oxford Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . 'Music Recommendation System Using Hybrid Approach', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 612-619. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Music_Recommendation_System_Using_Hybrid__Approach_ijariie21640.pdf (Accessed : 15 June 2025).
Harvard Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . (2023) 'Music Recommendation System Using Hybrid Approach', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 612-619IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Music_Recommendation_System_Using_Hybrid__Approach_ijariie21640.pdf (Accessed : 15 June 2025)
IEEE Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri , "Music Recommendation System Using Hybrid Approach," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 612-619, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Music_Recommendation_System_Using_Hybrid__Approach_ijariie21640.pdf [Accessed : 15 June 2025].
Turabian Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . "Music Recommendation System Using Hybrid Approach." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 (15 June 2025).
Vancouver Nekkanti Likhitha , Katepalli Yaswanth Sai Kumar , Nakka Venkata Durga Malleswari , and Kuchipudi Gayatri . Music Recommendation System Using Hybrid Approach. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : 15 June 2025]; 9(5) : 612-619. Available from: https://ijariie.com/AdminUploadPdf/Music_Recommendation_System_Using_Hybrid__Approach_ijariie21640.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 6/15/2025 7:05:54 PM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Music Recommendation based on Face Emotion Using Artificial Intelligence and Machine LearningInformation Science EngineeringDr. Sreenivasa Murthy V Download
SHADOW THE WEB BROWSERComputer Science and EngineeringLakshmi Narayan S Download
SECUHIRE – AI-POWERED INTERVIEW DETECTION SYSTEMComputer Engineering Tharun R Download
Early Detection Of Electrical Fault Line Using Artificial IntelligenceElectrical Engineering , Computer Science , Artificial IntelligenceRakshitha R Download
Real Time Object Detection Tracking using YOLO and Deep SORTInformation science and engineeringNandan M R Download
An AI-Integrated Intelligent Health Advisory System with Machine-Learning-Based Ayurvedic Formulation RecommendationInformation Science EngineeringSrinidhi G Download
Blockchain-Based Decentralized Medical Health Management System using Smart Contracts and IPFS Information Science and EngineeringVarun V Download
Precision Agriculture Using Machine Learning and IOTComputer Science and EngineeringRamesh B E Download
A Secure Blockchain Based Voting SystemComputer Science and EngineeringSagar K R Download
Chatbot based helpdesk for Government employee and departmentsComputer science & Engineering(Cyber Security Engineerting)Dr. Shanthi S Download
Zero Trust ArchitectureComputer EngineeringAditya Yanna Download
Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive ReviewComputer science and engineeringK Vijay kumar Download
Towards Efficient Resource Allocation and Request Scheduling in Quantum NetworksComputer Engineering Prajna Download
NEURAL NETWORK APPROACHES FOR DDOS ATTACK EFFECT ASSESSMENT: A SYSTEMATIC REVIEWComputer EngineeringAniketh Download
SMART TRAFFIC MANAGEMENT AND CONTROL SYSTEM BASED ON IOTComputer Science EngineeringPriyanka K Download
12