UGC Approved Journal no 63975(19)

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Published in:

Volume 5 Issue 12
December-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIREB06069


Registration ID:
233684

Page Number

560-566

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Title

Music Recommendation System based on Machine learning Technique

Abstract

AI has a sub-field which has made a huge impact in today’s world, known as machine learning. Structuring of the data is what the goal of it is. For being understandable and for the purpose of utilization by the user, machine learning fits the data-set into a model, which predict the output for unseen data. In today‘s time, with a great improvements in the field of technological aspects as well as streaming medias, various development has been done, like in music player the features like local playback , fast forward, reverse have been done. In this paper, a machine learning based technique is used to identify the emotion of the user and then recommend a song to the user.

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"Music Recommendation System based on Machine learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.560-566, December 2018, Available :http://www.jetir.org/papers/JETIREB06069.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Music Recommendation System based on Machine learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp560-566, December 2018, Available at : http://www.jetir.org/papers/JETIREB06069.pdf

Publication Details

Published Paper ID: JETIREB06069
Registration ID: 233684
Published In: Volume 5 | Issue 12 | Year December-2018
DOI (Digital Object Identifier):
Page No: 560-566
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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