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RETRACTED ARTICLE: Emotion-based music recommendation and classification using machine learning with IoT Framework

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This article was retracted on 27 December 2022

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Abstract

Technological advances integrating emotional maturity with established IoT systems are being examined with the emergence of the fourth industrial revolution. In this article, researchers propose an emotion-based music recommendation and classification framework (EMRCF) categorizing songs with high precision following individuals’ interpersonal team with memory and emotional songs. In specific, when adding new tunes to an IoT app fortune, methods must be developed that immediately categorize the characters based on people’s emotions . That’s one of the essential questions for project management. The empathic framework is used to research to identify emotional information. Musical characteristics can be derived from discussions in a micro-enterprise with the task force. Correlation analysis and supporting neural network is used to perform dynamic designation. The innovative prediction accuracy proposed recognizes most of the emotional responses triggered by music audience members and effectively categorizes songs. Furthermore, a comparison study is made with proposed algorithms such as decision trees, deep cognitive system and neighbor-closest, and relevance vector machines. The EMRCF reaches the prediction accuracy of 96.12% and the precision rate of 96.69%, which is not achieved by existing approaches.

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Acknowledgements

The authors would like to acknowledge the support of Taif University Researchers Supporting Project number (TURSP-2020/292), Taif University, Taif, Saudi Arabia. The authors also would like to acknowledge the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the fast-track Research Funding Program.

Funding

This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program. This work was supported by Taif University Researchers Supporting Project number (TURSP-2020/292), Taif University, Taif, Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science, College of Computing and Information Technology, University of Bisha, Bisha, Kingdom of Saudi Arabia

    Mohammad Tabrez Quasim & Mohammad Ayoub Khan

  2. Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Kingdom of Saudi Arabia

    Eman H. Alkhammash

  3. Department of Computer Science, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Kingdom of Saudi Arabia

    Myriam Hadjouni

Authors
  1. Mohammad Tabrez Quasim
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  2. Eman H. Alkhammash
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  3. Mohammad Ayoub Khan
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  4. Myriam Hadjouni
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Contributions

Conception and design of study: MTQ; Acquisition of data: EHA; Analysis and/or interpretation of data: MHK; Drafting the manuscript: MAK.

Corresponding author

Correspondence to Mohammad Ayoub Khan.

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I have no conflicts of interest to report regarding the present study.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by Vicente Garcia Diaz.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s00500-022-07786-2

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Quasim, M.T., Alkhammash, E.H., Khan, M.A. et al. RETRACTED ARTICLE: Emotion-based music recommendation and classification using machine learning with IoT Framework. Soft Comput 25, 12249–12260 (2021). https://doi.org/10.1007/s00500-021-05898-9

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  • DOI: https://doi.org/10.1007/s00500-021-05898-9

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