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An Intelligent Music Recommendation Framework for Multimedia Big Data: A Journey of Entertainment Industry

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Multimedia Technologies in the Internet of Things Environment, Volume 2

Part of the book series: Studies in Big Data ((SBD,volume 93))

Abstract

The digital media and entertainment industry are confronting new plans of action for how they make, advertise and circulate their substance. This is going on because the present purchasers search and access content anyplace, whenever and on any gadget. With the multiplication of online services and versatile innovations, the world has ventured into a media large information period. In this paper, a hybridized algorithm, namely particle swarm optimization-based crow search algorithm, is proposed for music recommendation system. The proposed model performed statistical analysis for a real dataset and takes into account most recent as well as past ratings of the users. Moreover, the contents of the items are considered while carrying out the particle swarm optimization. As a result, the data sparsity problem in recommenders is minimized substantially. The notion of hybridization guarantees a more personalized recommendation of music tracks. Finally, the proposed model is validated using Last.fm-360K dataset. The experimental results of the proposed model are compared with the existing model and provide Precision, Recall, F-measure and coverage values as 0.97, 0.97, 0.96 and 0.97, respectively.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, Atria Institute of Technology, Bangalore, India

    Manash Sarkar

  2. Amity University Rajasthan, Jaipur, India

    Arup Roy

  3. Pennsylvania State University, Great Valley, USA

    Youakim Badr

  4. Business Technical Analyst, ZS Associates, Pune, India

    Bhavya Gaur

  5. Electronics and Communication Engineering, SRM Institute of Science & Technology, Delhi-NCR, India

    Saptarshi Gupta

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  1. Manash Sarkar
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  2. Arup Roy
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  4. Bhavya Gaur
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  5. Saptarshi Gupta
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Editors and Affiliations

  1. Department of Computer Science and Engineering, GIET University, Gunupur, Odisha, India

    Raghvendra Kumar

  2. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Ghaziabad, Uttar Pradesh, India

    Rohit Sharma

  3. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

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Sarkar, M., Roy, A., Badr, Y., Gaur, B., Gupta, S. (2022). An Intelligent Music Recommendation Framework for Multimedia Big Data: A Journey of Entertainment Industry. In: Kumar, R., Sharma, R., Pattnaik, P.K. (eds) Multimedia Technologies in the Internet of Things Environment, Volume 2. Studies in Big Data, vol 93. Springer, Singapore. https://doi.org/10.1007/978-981-16-3828-2_3

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  • DOI: https://doi.org/10.1007/978-981-16-3828-2_3

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