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Leading music streaming platforms like Spotify, Gaana, and JioSaavn provide users with an extensive range of genres, enabling them to curate personal libraries. This research aims to enhance user interactivity and experience by employing accurate and intelligent music recommendation models. Collaborative filtering, content-based filtering, and hybrid models. A distinctive feature of this research is the incorporation of contextual elements such as location and time. The system intelligently detects the user’s location and recommends genres tailored to that specific context. Anticipated outcomes include the development of personalized music streaming journey of the user, addressing challenges of playlist creation, and ensuring that the system adapts seamlessly to users’ varying contexts. By considering factors like location and time, the research aims to make music recommendations not only accurate in terms of taste but also relevant to the user’s current situation. This holistic approach strives to create a dynamic and adaptable music streaming platform for a more immersive musical journey.

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Musical Theme Chord Recognition Using User Context Aware Information With Optimized KNN Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Ankita Acharya,
  • Rupal Yadav,
  • Sushruta Mishra,
  • Ankit Garg,
  • Ramy Riad Al-Fatlawy

摘要

Leading music streaming platforms like Spotify, Gaana, and JioSaavn provide users with an extensive range of genres, enabling them to curate personal libraries. This research aims to enhance user interactivity and experience by employing accurate and intelligent music recommendation models. Collaborative filtering, content-based filtering, and hybrid models. A distinctive feature of this research is the incorporation of contextual elements such as location and time. The system intelligently detects the user’s location and recommends genres tailored to that specific context. Anticipated outcomes include the development of personalized music streaming journey of the user, addressing challenges of playlist creation, and ensuring that the system adapts seamlessly to users’ varying contexts. By considering factors like location and time, the research aims to make music recommendations not only accurate in terms of taste but also relevant to the user’s current situation. This holistic approach strives to create a dynamic and adaptable music streaming platform for a more immersive musical journey.