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Intelligent Recommendation Model of Contemporary Pop Music Based on Knowledge Map

Zhang, Yan Ning, Xin ; Xin Ning

Computational intelligence and neuroscience, 2022, Vol.2022, p.1756585-8 [Periódico revisado por pares]

United States: Hindawi

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  • Título:
    Intelligent Recommendation Model of Contemporary Pop Music Based on Knowledge Map
  • Autor: Zhang, Yan
  • Ning, Xin ; Xin Ning
  • Assuntos: Algorithms ; Big Data ; Datasets ; Digital music ; Information overload ; Information services ; Intelligence ; Internet ; Knowledge ; Knowledge representation ; Listening ; Music ; Overloading ; Peer to peer computing ; Popular music ; Recommender systems ; Semantics ; User behavior
  • É parte de: Computational intelligence and neuroscience, 2022, Vol.2022, p.1756585-8
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Academic Editor: Xin Ning
  • Descrição: With the advent of the era of big data, the rise of Web2.0 completely subverts the traditional Internet model and becomes the trend of today’s information age. Simultaneously, massive amounts of data and information have infiltrated various Internet companies, resulting in an increase in the problem of information overload. In the online world, learning how to quickly and accurately select the parts we are interested in from a variety of data has become a hot topic. Intelligent music recommendation has become a current research hotspot in music services as a viable solution to the problem of information overload in the digital music field. On the basis of precedents, this paper examines the characteristics of music in a comprehensive and detailed manner. A knowledge graph-based intelligent recommendation algorithm for contemporary popular music is proposed. User-defined tags are described as the free genes of music in this paper, making it easier to analyze user behavior and tap into user interests. It has been confirmed that this algorithm’s recommendation quality is relatively high, and it offers a new development path for improving the speed of searching for health information services.
  • Editor: United States: Hindawi
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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