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  Subjects -> CONSERVATION (Total: 128 journals)
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International Journal of Social Ecology and Sustainable Development
Journal Prestige (SJR): 0.131
Number of Followers: 3  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 1947-8402 - ISSN (Online) 1947-8410
Published by IGI Global Homepage  [147 journals]
  • Content-Based Music Recommendation Using Non-Stationary Bayesian
           Reinforcement Learning

    • Free pre-print version: Loading...

      Abstract: This paper presents a music recommendation system for the offline libraries of songs that employs the concepts of reinforcement learning to obtain satisfactory recommendations based on the various considered content-based parameters. In order to obtain insights about the effectiveness of the generated recommendations, parallel instances of single-play multi-arm bandit algorithms are maintained. In conjunction to this, the concepts of Bayesian learning are considered to model the user preferences, by assuming the environment’s reward generating process to be non-stationary and stochastic. The system is designed to be simple, easy to implement, and at-par with the user satisfaction, within the bounds of the input data capabilities.
      Keywords: Environmental Science and Technologies; Environment & Agriculture; Sustainable Development
      Citation: International Journal of Social Ecology and Sustainable Development (IJSESD), Volume: 13, Issue: 9 (2022) Pages: 0-0
      PubDate: 2022-01-04T05:00:00Z
      DOI: 10.4018/IJSESD.292048
      Issue No: Vol. 13, No. 9 (2022)
       
  • Content-Based Music Recommendation Using Non-Stationary Bayesian
           Reinforcement Learning

    • Free pre-print version: Loading...

      Abstract: This paper presents a music recommendation system for the offline libraries of songs that employs the concepts of reinforcement learning to obtain satisfactory recommendations based on the various considered content-based parameters. In order to obtain insights about the effectiveness of the generated recommendations, parallel instances of single-play multi-arm bandit algorithms are maintained. In conjunction to this, the concepts of Bayesian learning are considered to model the user preferences, by assuming the environment’s reward generating process to be non-stationary and stochastic. The system is designed to be simple, easy to implement, and at-par with the user satisfaction, within the bounds of the input data capabilities.
      Keywords: Environmental Science and Technologies; Environment & Agriculture; Sustainable Development
      Citation: International Journal of Social Ecology and Sustainable Development (IJSESD), Volume: 13, Issue: 9 (2022) Pages: 0-0
      PubDate: 2022-01-04T05:00:00Z
      DOI: 10.4018/IJSESD.292051
      Issue No: Vol. 13, No. 9 (2022)
       
  • Content-Based Music Recommendation Using Non-Stationary Bayesian
           Reinforcement Learning

    • Free pre-print version: Loading...

      Authors: Bharadwaj; Brijgopal, Selvanambi, Ramani, Karuppiah, Marimuthu, Poonia, Ramesh Chandra
      Pages: 1 - 18
      Abstract: This paper presents a music recommendation system for the offline libraries of songs that employs the concepts of reinforcement learning to obtain satisfactory recommendations based on the various considered content-based parameters. In order to obtain insights about the effectiveness of the generated recommendations, parallel instances of single-play multi-arm bandit algorithms are maintained. In conjunction to this, the concepts of Bayesian learning are considered to model the user preferences, by assuming the environment’s reward generating process to be non-stationary and stochastic. The system is designed to be simple, easy to implement, and at-par with the user satisfaction, within the bounds of the input data capabilities.
      Keywords: Environmental Science and Technologies; Environment & Agriculture; Sustainable Development
      Citation: International Journal of Social Ecology and Sustainable Development (IJSESD), Volume: 13, Issue: 9 (2022) Pages: 1-18
      PubDate: 2022-01-04T05:00:00Z
      DOI: 10.4018/IJSESD.292053
      Issue No: Vol. 13, No. 9 (2022)
       
 
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