Predicting Song Likability: A Regression Approach Using User Demographics and Qualitative Feedback-Reference-Cited by-同舟云学术

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Predicting Song Likability: A Regression Approach Using User Demographics and Qualitative Feedback

Published:2023-11-24 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 2nd International Conference on Futuristic Technologies (INCOFT)
language:
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Author:

Bachal Anish¹,Kumar Ashwin²,Bachal Tarush²,Gutte Vitthal S.³^ORCID

Affiliation:

1. MIT World Peace University,Department of Electronics and Communication Engineering,Pune,Maharashtra

2. MIT World Peace University,Department of Computer Engineering & Technology,Pune,Maharashtra

3. Dr. Vishwanath Karad MIT World, Peace University,Department of Computer Engineering and Technology,Pune,Maharashtra,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424959/10424987/10425523.pdf?arnumber=10425523

Reference10 articles.

1. T-RECSYS: A Novel Music Recommendation System Using Deep Learning

2. A content-based system for music recommendation and visualization of user preferences working on semantic notions

3. Exploiting the emotional preference of music for music recommendation in daily activities

4. Novel Datasets for Evaluating Song Popularity Prediction Tasks

5. Predicting Song Success: Understanding Track Features and Predicting Popularity Using Spotify Data

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