基于深度学习神经网络的钢琴曲推荐算法

Yang Si
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引用次数: 1

摘要

随着人们生活质量的提高,音乐文化在人们的日常生活中迅速发展。钢琴作为欧洲的代表音乐,其发展与民族文化密切相关。现在它越来越受欢迎,已经成为中国时尚的一个组成部分。随着数字音乐数量的快速增长,如何在海量音乐中找到自己喜欢的音乐已经成为困扰用户的难题。音乐推荐系统是目前解决这一问题的最佳途径。它可以向用户推荐用户喜欢的歌曲,为歌曲找到合适的目标用户。音乐推荐算法通过分析音乐点播的历史行为,减少用户的信息疲劳,提高用户体验。本文以基于内容的推荐为主要思想,研究了基于深度学习技术的钢琴数字音乐推荐算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Piano music recommendation algorithm based on deep learning neural network
With the improvement of people’s quality of life, music culture develops rapidly in people’s daily life. Piano, as the representative music of Europe, its development is closely related to national culture. Now its popularity is increasing, and it has become one of the components of Chinese fashion. With the rapid growth of the number of digital music, how to find their favorite music in massive music has become a problem for users. Music recommendation system is the best way to solve this problem at present. It can recommend songs that users like to users and find suitable target users for songs. Music recommendation algorithm can reduce users’ information fatigue and improve users’ experience by analyzing the historical behavior of music on demand. This paper takes contentbased recommendation as the main idea, and studies the piano digital music recommendation algorithm based on deep learning technology.
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