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    • 2. 发明申请
    • METHODS AND SYSTEMS FOR DETERMINING QUERY DATE RANGES
    • 确定查询日期范围的方法和系统
    • US20170024388A1
    • 2017-01-26
    • US14804835
    • 2015-07-21
    • Yahoo!, Inc.
    • Frank Richard BentleyJoseph Nathaniel KayeDavid Ayman ShammaJohn Alexis Guerra Gomez
    • G06F17/30
    • G06F16/9537
    • One or more systems and/or methods for determining a query date range and/or searching a content corpus are provided. A set of content items (e.g., digital images, videos, etc.), associated with an event, may be identified from a content corpus. The set of content items may be evaluated to identify temporal features (e.g., digital time stamps) for the set of content items. A query date range for the event may be determined based upon the temporal features (e.g., users may capture photos that are related to Christmas from December 4th to December 27th). In an example, responsive to receiving a search query, associated with the event, the search query may be adjusted based upon the query date range to create an adjusted search query. The content corpus may be searched using the adjusted search query to create search query results for the search query.
    • 提供了一种或多种用于确定查询日期范围和/或搜索内容语料库的系统和/或方法。 可以从内容语料库识别与事件相关联的一组内容项目(例如,数字图像,视频等)。 可以评估该组内容项目以识别该组内容项目的时间特征(例如,数字时间戳)。 可以基于时间特征来确定事件的查询日期范围(例如,用户可以从12月4日至12月27日捕获与圣诞节相关的照片)。 在一个示例中,响应于接收到与事件相关联的搜索查询,可以基于查询日期范围来调整搜索查询以创建经调整的搜索查询。 可以使用经调整的搜索查询来搜索内容语料库以创建搜索查询的搜索查询结果。
    • 3. 发明申请
    • PREDICTING CONTENT CONSUMPTION
    • 预测内容消费
    • US20160335645A1
    • 2016-11-17
    • US14710096
    • 2015-05-12
    • Yahoo!, Inc.
    • Christian HolzFrank Richard BentleyAyman Farahat
    • G06Q30/02G06Q10/06
    • Methods and systems for predicting content consumption are provided herein. An application log of a user, comprising a user's application data, and a viewing log of the user, comprising the user's viewing data (e.g., television programs watched by the user), may be evaluated over a time period to construct a model. The model may comprise a correlation between the viewing log and the application log during the time period (e.g., what applications the user interacts with while watching a program). Second application data, regarding application usage of a second user, may be extracted. The model may be applied to the second application data to identify an expected viewing action of the second user (e.g., what program the second user is likely to watch during the time period based upon applications used by the second user). The second user may be provided with content related to the expected viewing action.
    • 本文提供了预测内容消费的方法和系统。 包括用户的观看数据(例如,用户观看的电视节目)的用户的应用程序日志,包括用户的应用数据和观看日志可以在一段时间内被评估以构建模型。 该模型可以包括在该时间段期间的观看日志和应用日志之间的相关性(例如,用户在观看节目时进行交互时的什么应用)。 可以提取关于第二用户的应用使用的第二应用数据。 该模型可以应用于第二应用数据以识别第二用户的预期观看动作(例如,基于第二用户使用的应用,第二用户在该时间段期间可能观看的程序)。 可以向第二用户提供与预期观看动作相关的内容。