IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 9

Issue Published : 96

Article Submitted :

Article Published :

Total Authors :

Total Reviewer :

Total Countries :

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Recommendation system for song data using K-Means and K-Medoids Clustering algorithms
Authors Name: B.Anoohya , J Nikitha , Dr P Naga Jyothi , I Anish , G Bhargavi
Download E-Certificate: Download
Author Reg. ID:
IJNRD_189881
Published Paper Id: IJNRD2303467
Published In: Volume 8 Issue 3, March-2023
DOI:
Abstract: The ability to anticipate user preferences is crucial to recommendation systems. A personalized recommendation must take into account the listener's existing musical preferences as well as any changes to the "kind" of songs. This paper proposes a personalized next-song recommendation system. It utilizes Web API for Spotify to record the song features. K-means and K-medoids clustering algorithms are employed to identify similar songs using attributes. It is identified to which cluster the input music belongs. Content-based clustering is the term used for this. By computing the similarity measure, the songs that are "near" to the input song are identified next. Based on popularity metrics for this list of songs, the set of songs that should be played in order are identified.
Keywords: clustering, Recommendation, K-Means, K-medoids
Cite Article: "Recommendation system for song data using K-Means and K-Medoids Clustering algorithms", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e530-e533, March-2023, Available :http://www.ijnrd.org/papers/IJNRD2303467.pdf
Downloads: 000118791
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD2303467
Registration ID: 189881
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: e530-e533
Country: Visakhapatnam, Andhra Pradesh, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2303467
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2303467
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD