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1. 发明授权

US09875245B2 Content item recommendations based on content attribute sequence 有权
公开(公告)号：US09875245B2
公开(公告)日：2018-01-23
申请号：US14684063
申请日：2015-04-10
申请人： Apple Inc.
发明人： Daniel Cartoon , Mark H. Levy
IPC分类号： G06F17/30
CPC分类号： G06F17/30053
摘要： User created playlists can be analyzed to create a statistical language model indicating the likelihood that a particular sequence of content attributes will be found in a playlist created by a user, as well as the likelihood of any sequence of one or more content attributes following a playlist or partial playlist created by a user. The language model can be used to generate a recommended content attribute sequence based on a partial playlist of one or more content items. A recommended content item sequence that will be pleasant to a user when added to the partial playlist can be selected based on the recommended content attribute sequence.

2. 发明申请

US20170357479A1 PERSONAL MUSIC CONTENT 审中-公开
公开(公告)号：US20170357479A1
公开(公告)日：2017-12-14
申请号：US15273428
申请日：2016-09-22
申请人： Apple Inc.
发明人： Arvind S. Shenoy , Alfredo Ramos-Alvarez , Cody D. Jorgensen , Daniel Cartoon , Mark H. Levy , Matthias Mauch , Paul C. Irvine , Priyo Mustafi , Thomas Alsina
IPC分类号： G06F3/16 , G06T13/80 , G06F3/0482
CPC分类号： G06F3/167 , G06F3/165
摘要： The present technology pertains to automatically providing refreshed versions of personalized playlists of media items based on a refresh schedule. The automatically refreshed personalized playlists can be automatically downloaded to a client device associated with the user account. In some embodiments an animation can be presented to show that a playlist was automatically refreshed. The automatically refreshed personalized playlist can be created based on an assumption that playlists are a collection of media items that go well together in a collection.

3. 发明申请

US20210256056A1 Automatically Predicting Relevant Contexts For Media Items 有权
公开(公告)号：US20210256056A1
公开(公告)日：2021-08-19
申请号：US17188858
申请日：2021-03-01
申请人： Apple Inc.
发明人： Mark H. Levy , Arvind S. Shenoy , Matthias Mauch , Daniel Cartoon
IPC分类号： G06F16/683 , G06N3/08 , G06F16/635 , G06F16/638 , G06N3/04
摘要： The present technology pertains to automatically context labeling media items with relevant contexts, and further for algorithmically generating high quality playlists built around a context that are personalized to a profile of an account. This is accomplished by combining data from observed playlists, and data representing intrinsic properties of media items to predict contexts for media items.

4. 发明申请

US20200004495A1 Generating a Customized Social-Driven Playlist 审中-公开
公开(公告)号：US20200004495A1
公开(公告)日：2020-01-02
申请号：US16454668
申请日：2019-06-27
申请人： Apple Inc.
发明人： Bekir B. Dundar , Arvind S. Shenoy , Daniel Cartoon , Denise L. Chen , Drew R. Domm , Fredric R. Vinna , Mark H. Levy , Paul C. Irvine , Priyo Mustafi , Thomas Alsina , Erik Lindholm , Uli M. Schoberl
IPC分类号： G06F3/16 , H04L29/08 , G06F3/0482 , G06F16/638 , G06F16/2457
摘要： Generating a customized playlist may include identifying a user account for which a playlist is to be generated, where the user account is associated with a user listening history, a taste profile, and a social profile, identifying one or more friend accounts linked to the user account based on the social profile, obtaining an indication of a plurality of songs associated with one or more of the friend accounts, determining a listening history for the one or more plurality of songs based on the friend accounts, obtaining a subset of the plurality of songs based on the listening history of the plurality of songs, and generating a playlist from the subset of the plurality of songs.

5. 发明授权

US10936653B2 Automatically predicting relevant contexts for media items 有权
公开(公告)号：US10936653B2
公开(公告)日：2021-03-02
申请号：US15720880
申请日：2017-09-29
申请人： Apple Inc.
发明人： Mark H. Levy , Arvind S. Shenoy , Matthias Mauch , Daniel Cartoon
IPC分类号： G06F7/00 , G06F17/30 , G06F16/683 , G06N3/08 , G06F16/635 , G06F16/638 , G06N3/04 , G06N20/20 , G06N5/00
摘要： The present technology pertains to automatically contextlabeling media items with relevant contexts, and further for algorithmically generating high quality playlists built around a context that are personalized to a profile of an account. This is accomplished by combining data from observed playlists, and data representing intrinsic properties of media items to predict contexts for media items.

6. 发明申请

US20190079935A1 STEERING FOR UNSTRUCTURED MEDIA STATIONS 审中-公开
公开(公告)号：US20190079935A1
公开(公告)日：2019-03-14
申请号：US15885047
申请日：2018-01-31
申请人： APPLE INC.
发明人： Mark H. Levy , Jan Markus Harrie Van Balen , Arvind S. Shenoy , Matthias Mauch , Daniel Cartoon
IPC分类号： G06F17/30 , G06F15/18 , G06K9/62
摘要： The present technology pertains to steering a playlisting service toward media items that are likely to receive positive feedback from a user operating a client device. The present technology permits a request to play media items without requiring an input context. A playlist service can begin to receive feedback on the playback of the media items and the received playback can be utilized by a steering service in response to a steering request to identify media items for playback that are likely to receive positive feedback based on the feedback received on a sequence of previously played media items.

7. 发明申请

US20180349492A1 Automatically Predicting Relevant Contexts For Media Items 审中-公开
公开(公告)号：US20180349492A1
公开(公告)日：2018-12-06
申请号：US15720880
申请日：2017-09-29
申请人： Apple Inc.
发明人： Mark H. Levy , Arvind S. Shenoy , Matthias Mauch , Daniel Cartoon
IPC分类号： G06F17/30 , G06N3/08
摘要： The present technology pertains to automatically contextlabeling media items with relevant contexts, and further for algorithmically generating high quality playlists built around a context that are personalized to a profile of an account. This is accomplished by combining data from observed playlists, and data representing intrinsic properties of media items to predict contexts for media items.

8. 发明申请

US20160299906A1 Content Item Recommendations Based On Content Attribute Sequence 有权
标题翻译：基于内容属性序列的内容项目建议
公开(公告)号：US20160299906A1
公开(公告)日：2016-10-13
申请号：US14684063
申请日：2015-04-10
申请人： Apple Inc.
发明人： Daniel Cartoon , Mark H. Levy
IPC分类号： G06F17/30
CPC分类号： G06F17/30053
摘要： User created playlists can be analyzed to create a statistical language model indicating the likelihood that a particular sequence of content attributes will be found in a playlist created by a user, as well as the likelihood of any sequence of one or more content attributes following a playlist or partial playlist created by a user. The language model can be used to generate a recommended content attribute sequence based on a partial playlist of one or more content items. A recommended content item sequence that will be pleasant to a user when added to the partial playlist can be selected based on the recommended content attribute sequence.
摘要翻译：可以分析用户创建的播放列表以创建统计语言模型，指示在用户创建的播放列表中将找到特定的内容属性序列的可能性，以及播放列表之后的一个或多个内容属性的任何序列的可能性或由用户创建的部分播放列表。语言模型可以用于基于一个或多个内容项的部分播放列表生成推荐的内容属性序列。可以基于推荐的内容属性序列来选择在添加到部分播放列表时对于用户而言愉快的推荐内容项序列。

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