Data Exploration and Predictive Analytics for Music Publishing

音乐出版的数据探索和预测分析

• 批准号: 101948
• 金额: $ 26.76万
• 依托单位: SENTRIC MUSIC LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=101948
• 关键词: Data; Exploration; Predictive; Analytics; Music

Our project is to create tools for predictive modeling and data visualisation for use in the music publishing industry. These tools and algorithms that will enable predictive modeling based on data drawn from a wide variety of sources, including song registrations, royalty reports, streaming media, social media, and crowdsourced reviews. We plan to use these tools to identify artists (or their individual tracks) that have the potential to achieve widespread popularity, identify instances where royalties may be underreported, and to determine whether an artist's royalty streams are sufficiently stable so as to allow us to advance funds against them. We also plan to deliver the benefits of this project into our users' hands by providing them with predictive analytics tools delivered online and via mobile apps. These tools will provide them with data visualisation capabilities and allow them to query our database in ways that may yield valuable insights regarding their own songs and musical industry careers and help them think strategically about the creation and exploitation of their songs and other musical works.

我们的项目是创建用于音乐出版行业的预测建模和数据可视化工具。这些工具和算法将基于从各种来源获取的数据进行预测建模，包括歌曲注册、版税报告、流媒体、社交媒体和众包评论。我们计划使用这些工具来识别有可能获得广泛流行的艺术家（或他们的个人曲目），识别版税可能被低估的情况，并确定艺术家的版税流是否足够稳定，以便我们能够提前支付资金。我们还计划通过为用户提供在线和通过移动的应用程序提供的预测分析工具，将该项目的好处传递到用户手中。这些工具将为他们提供数据可视化功能，并允许他们查询我们的数据库，这些数据库可能会对他们自己的歌曲和音乐行业的职业生涯产生有价值的见解，并帮助他们从战略上思考他们的歌曲和其他音乐作品的创作和利用。