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Preface to the Special Issue on user modeling for personalized interaction with music

机译：与音乐个性化互动的用户建模特殊问题

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摘要

Music search, retrieval, and recommendation systems have experienced a boom during the past few years due to streaming services providing access to huge catalogs anywhere and anytime. These streaming services collect the user behavior in terms of actions on music items, such as play, skip, playlist creation, and modification. As a result, an abundance of user and usage data has been collected and is available to companies and academics, allowing for user profiling and to create personalized music search and recommendation systems. The importance and timeliness of research on such personalized music systems is evidenced by publications in venues including the ACM Conference on Recommender Systems, ACM Conference on User Modeling, Adaptation and Personalization, International Society for Music Information Retrieval Conference, the ACM Special Interest Group on Information Retrieval Conference, ACM CHI Conference on Human Factors in Computing Systems, and the ACM International Conference on Intelligent User Interfaces, as well as in journals including IEEE Transactions on Affective Computing and ACM Transactions on Intelligent Systems and Technology, in addition to UMUAI.
机译：由于流媒体服务，在过去几年中，音乐搜索，检索和推荐系统在任何地方和随时随地提供了巨大目录的速度。这些流服务在音乐项目的操作项中收集用户行为，例如播放，跳过，播放列表创建和修改。因此，已经收集了丰富的用户和使用数据，并可提供公司和学者，允许用户分析并创建个性化音乐搜索和推荐系统。场馆的出版物在包括推荐制度的ACM会议上的出版物，ACM会议关于用户建模，适应和个性化，国际音乐信息检索会议，ACM特殊兴趣集团信息的国际社会检索会议，ACM Chi关于计算系统人类因素的会议，以及ACM智能用户界面的国际会议，以及在智能系统和技术上的情感计算和ACM交易包括IEEE交易，包括IEEE交易，以及Umuai。

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  • 来源
    《User modeling and user-adapted interaction》 |2020年第2期|195-198|共4页
  • 作者

    Marko Tkalčič; Markus Schedl; Peter Knees;

  • 作者单位

    University of Primorska Glagoljaska 8 Koper Slovenia;

    Johannes Kepler University Linz (JKU) and Linz Institute of Technology (LIT) Altenberger Straße 69 4040 Linz Austria;

    TU Wien Favoritenstraße 9-11/194-1 1040 Vienna Austria;

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