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    System and method for adaptive media playback based on destination
    31.
    发明授权
    System and method for adaptive media playback based on destination 有权
    基于目的地的自适应媒体播放的系统和方法

    公开(公告)号：US09390757B2

    公开(公告)日：2016-07-12

    申请号：US14703073

    申请日：2015-05-04

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Behzad Shahraray ,  Andrea Basso ,  Lee Begeja ,  David C. Gibbon ,  Zhu Liu ,  Bernard S. Renger

    IPC: G06F17/30 ,  G11B27/10 ,  G11B27/00 ,  G11B27/034

    CPC classification number: G06Q30/0261 ,  G01C21/3697 ,  G11B27/005 ,  G11B27/034 ,  G11B27/105 ,  H04L67/18 ,  H04N5/783

    Abstract: Disclosed herein are systems, methods, and computer readable-media for adaptive media playback based on destination. The method for adaptive media playback comprises determining one or more destinations, collecting media content that is relevant to or describes the one or more destinations, assembling the media content into a program, and outputting the program. In various embodiments, media content may be advertising, consumer-generated, based on real-time events, based on a schedule, or assembled to fit within an estimated available time. Media content may be assembled using an adaptation engine that selects a plurality of media segments that fit in the estimated available time, orders the plurality of media segments, alters at least one of the plurality of media segments to fit the estimated available time, if necessary, and creates a playlist of selected media content containing the plurality of media segments.

    Abstract translation: 本文公开了用于基于目的地的自适应媒体回放的系统，方法和计算机可读介质。 用于自适应媒体播放的方法包括确定一个或多个目的地，收集与一个或多个目的地相关或描述一个或多个目的地的媒体内容，将媒体内容组合成节目并输出该节目。 在各种实施例中，媒体内容可以是基于实时事件的广告，消费者生成的，基于时间表，或被组合以适合估计的可用时间。 可以使用适配引擎来组合媒体内容，该适配引擎选择适合估计的可用时间的多个媒体片段，对多个媒体片段进行排序，如果需要，改变多个媒体片段中的至少一个以适合估计的可用时间 并且创建包含多个媒体片段的所选媒体内容的播放列表。

    System and method for generating media bookmarks
    32.
    发明授权
    System and method for generating media bookmarks 有权

    公开(公告)号：US09342596B2

    公开(公告)日：2016-05-17

    申请号：US14737683

    申请日：2015-06-12

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Behzad Shahraray ,  Andrea Basso ,  Lee Begeja ,  David C. Gibbon ,  Zhu Liu ,  Bernard S. Renger

    IPC: G06F17/30

    CPC classification number: G06F17/30784 ,  G06F17/3082 ,  G06F17/30849 ,  G06F17/30858 ,  G06F17/30876 ,  G06F17/30884 ,  G11B27/005 ,  G11B27/34

    Abstract: Disclosed herein are systems, methods, and computer-readable media for transmedia video bookmarks, the method comprising receiving a first place marker and a second place marker for a segment of video media, extracting metadata from the video media between the first and second place markers, normalizing the extracted metadata, storing the normalized metadata, first place marker, and second place marker as a video bookmark, and retrieving the media represented by the video bookmark upon request from a user. Systems can aggregate video bookmarks from multiple sources and refine the first place marker and second place marker based on the aggregated video bookmarks. Metadata can be extracted by analyzing text or audio annotations. Metadata can be normalized by generating a video thumbnail representing the video media between the first place marker and the second place marker. Multiple video bookmarks may be searchable by metadata or by the video thumbnail visually.

    Comprehensive Information Market Exchange
    36.
    发明申请
    Comprehensive Information Market Exchange 有权
    综合信息市场交流

    公开(公告)号：US20130080209A1

    公开(公告)日：2013-03-28

    申请号：US13681697

    申请日：2012-11-20

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Lee Begeja ,  David C. Gibbon ,  Paul van Vleck

    IPC: G06Q30/02

    CPC classification number: G06Q30/0201 ,  G06Q40/12 ,  G06Q99/00

    Abstract: Systems and techniques for collecting information as authorized by information providers and sharing the information with information recipients according to criteria specified by the information providers. Information is collected from one or more of a variety of sources and stored in a provider profile, with the provider profile also specifying criteria for sharing the information, including payment required for sharing the information with particular categories of recipients. An exchange system is maintained allowing recipients to request or to otherwise specify needs for particular categories of information and payments to be provided by the information, and needs or requests of recipients for information are matched with criteria specified by providers, with information being transferred or used to provide results for a recipient and payment being transferred from the recipient to a provider or providers when a match between information needs and criteria for sharing information is identified.

    Abstract translation: 根据信息提供者规定的标准，收集信息提供者授权的信息并与信息收发者共享信息的系统和技术。 信息从一种或多种来源收集并存储在提供者简档中，提供者简档也指定用于共享信息的标准，包括与特定类别的收件人共享信息所需的付款。 保持交换系统，允许收件人请求或另外指定由信息提供的特定类别的信息和付款的需求，并且信息的接收者的需求或请求与提供者指定的标准相匹配，信息被转移或使用 在信息需求和共享信息标准之间的匹配被识别时，为收件人和从接收者转移到提供者或提供者的付款提供结果。

    Machine learning model understanding as-a-service
    37.
    发明授权
    Machine learning model understanding as-a-service 有权

    公开(公告)号：US11995518B2

    公开(公告)日：2024-05-28

    申请号：US15849115

    申请日：2017-12-20

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Eric Zavesky ,  David Crawford Gibbon ,  Lee Begeja ,  Paul Triantafyllou ,  Behzad Shahraray

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: Concepts and technologies disclosed herein are directed to machine learning model understanding as-a-service. According to one aspect of the concepts and technologies disclosed herein, a model understanding as-a-service system can receive, from a user system, a service request that includes a machine learning model created for a user associated with the user system. The model understanding as-a-service system can conduct an analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can compile, for the user, results of the analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can create a service response that includes the results of the analysis. The model understanding as-a-service system can provide the service response to the user system.

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