METHOD AND APPARATUS FOR CURATION OF CONTENT

    公开(公告)号:US20210026902A1

    公开(公告)日:2021-01-28

    申请号:US16520199

    申请日:2019-07-23

    Abstract: Systems and methods for curation of content, such as e-learning content or online instructional materials, according to particular criteria such as the amount of pictorial representations contained therein, the amount of verbal expression contained therein, and whether the content contains a summary. Other criteria may also be employed. Users may select any one or more of these and other criteria. Content is then sorted according to the selected criteria and presented as an ordered list of content that users can select for viewing.

    Systems and methods for adjusting storage based on determining content item popularity

    公开(公告)号:US12132798B2

    公开(公告)日:2024-10-29

    申请号:US18530956

    申请日:2023-12-06

    CPC classification number: H04L67/535 H04L67/306 H04L67/54

    Abstract: Systems and associated methods are described for determining popularity of new content. The system analyzes a content item to identify at least a first and a second attribute associated with the content item. The system also identifies previously posted content items associated with the first and the second attributes. The system then determines levels of user activity associated with the previously posted content item corresponding to the first attribute over a first past time period and associated with the previously posted content item corresponding to the second attribute over a second past time period. The system then extrapolates a levels of user activity for a future time period based on the first past time period and on the second past time period. The system further determines an anticipated level of user activity associated with the content item for the future time period based on the extrapolated levels of user activity.

    CUSTOMIZED PASSTHROUGH
    77.
    发明公开

    公开(公告)号:US20240212288A1

    公开(公告)日:2024-06-27

    申请号:US18088325

    申请日:2022-12-23

    Abstract: System and methods for customizing passthrough feed are disclosed. Expected VR content and predicted user movements in a real-world environment are determined based on recently rendered VR content, user activity data, and real-world scenes. When passthrough feed is enabled, it may be customized based on the expected VR content and predicted user movements. Customization techniques comprising custom style filters, style transfer neural networks, and adding VR content elements to the passthrough feed display window may be used to customize the passthrough feed to match the style of the VR content. The use of the customization techniques may be based on one of or a combination of a duration during which the passthrough feed is activated, the color intensity difference between the realities, an event or purpose which triggered activation of the passthrough feed, or a size of a display window of the passthrough feed relative to the VR content.

    Systems and methods for adjusting storage based on determining content item popularity

    公开(公告)号:US11888951B2

    公开(公告)日:2024-01-30

    申请号:US17983141

    申请日:2022-11-08

    CPC classification number: H04L67/535 H04L67/306 H04L67/54

    Abstract: Systems and associated methods are described for determining popularity of new content. The system analyzes a content item to identify at least a first and a second attribute associated with the content item. The system also identifies previously posted content items associated with the first and the second attributes. The system then determines levels of user activity associated with the previously posted content item corresponding to the first attribute over a first past time period and associated with the previously posted content item corresponding to the second attribute over a second past time period. The system then extrapolates a levels of user activity for a future time period based on the first past time period and on the second past time period. The system further determines an anticipated level of user activity associated with the content item for the future time period based on the extrapolated levels of user activity.

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