PERSONALIZING USER INTERFACE (UI) ELEMENTS
    2.
    发明申请
    PERSONALIZING USER INTERFACE (UI) ELEMENTS 审中-公开
    个性化用户界面(UI)元素

    公开(公告)号:US20160259840A1

    公开(公告)日:2016-09-08

    申请号:US14405971

    申请日:2014-10-16

    Applicant: Yahoo! Inc.

    Abstract: This disclosure relates to personalizing user interface (UI) elements of online content (a website, a mobile application, etc.) presented on a user device. The UI personalization technique may include, for a current online session, processing user-related data and context-related data to determine the UI element(s) and their attribute value(s) to be used for presentation of the online content during the current session. The user-related data include information regarding the user/user device, and the context data may include details about the online content (content type/topic, default UI attribute values, etc.) being accessed in the given online session. The user data and the context data may be processed based on modeling data related to users and their interaction with the UI of online content from different publishers and/or advertisers. Based on such processing, personalized UI element(s) and attribute values are determined and the online content is presented with the personalized UI.

    Abstract translation: 本公开涉及个性化在用户设备上呈现的在线内容(网站,移动应用等)的用户界面(UI)元素。 UI个性化技术可以包括对于当前的在线会话,处理用户相关数据和上下文相关数据以确定在当前期间用于在线内容的呈现的UI元素及其属性值 会话 用户相关数据包括关于用户/用户设备的信息,并且上下文数据可以包括在给定在线会话中被访问的在线内容(内容类型/主题,默认UI属性值等)的细节。 可以基于与用户相关的建模数据及其与来自不同发布者和/或广告商的在线内容的UI的交互来处理用户数据和上下文数据。 基于这样的处理,确定个性化UI元素和属性值,并且使用个性化UI呈现在线内容。

    Method and System for Enhanced Content Recommendation
    3.
    发明申请
    Method and System for Enhanced Content Recommendation 审中-公开
    增强内容推荐方法与系统

    公开(公告)号:US20160188725A1

    公开(公告)日:2016-06-30

    申请号:US14586202

    申请日:2014-12-30

    Applicant: Yahoo! Inc.

    Abstract: Method, system, and programs for providing content recommendation are disclosed. A first set of candidate content items may be generated based on a user profile, and a second set of candidate items may be generated based on the likelihood that the user will click a corresponding candidate content item in the second set. The candidate content items in the first and second sets may be ranked together using a learning model and presented to the user as content recommendations based on their rankings. The likelihood that the user will click a given candidate content item in the second set may be estimated based on similarities between the given content item and content items related to the given content item. Such a similarity may be computed based on activities performed by users who have viewed both the given content item and a related content item.

    Abstract translation: 公开了用于提供内容推荐的方法,系统和程序。 可以基于用户简档来生成第一组候选内容项,并且可以基于用户将点击第二组中的相应候选内容项的可能性来生成第二组候选项。 可以使用学习模型将第一和第二组中的候选内容项目排列在一起,并且基于其排名将其呈现给用户作为内容推荐。 可以基于给定内容项和与给定内容项相关的内容项之间的相似度来估计用户点击第二组中的给定候选内容项的可能性。 可以基于同时观看给定内容项目和相关内容项目的用户执行的活动来计算这样的相似度。

    SYSTEMS AND METHODS FOR A UNIFIED AUDIENCE TARGETING SOLUTION
    4.
    发明申请
    SYSTEMS AND METHODS FOR A UNIFIED AUDIENCE TARGETING SOLUTION 审中-公开
    用于统一的听觉目标解决方案的系统和方法

    公开(公告)号:US20150186932A1

    公开(公告)日:2015-07-02

    申请号:US14144130

    申请日:2013-12-30

    Applicant: Yahoo! Inc.

    Inventor: Jian XU Yu Zou

    CPC classification number: G06Q30/0251 G06Q30/0269

    Abstract: Systems and methods for providing a unified targeting solution are disclosed. The system obtains user data for each user in a user group from a database stored in the non-transitory storage medium. The database is organized on a user by user basis and includes signals from a plurality of sources. The system receives an input from an advertiser including a marketing intention. The system includes features extracted from the user data and the input. The system obtains a score for each user based on the extracted features. The system selects users from the user group based on the obtained scores.

    Abstract translation: 公开了提供统一定位解决方案的系统和方法。 该系统从存储在非暂时性存储介质中的数据库中获取用户组中的每个用户的用户数据。 数据库以用户为基础组织在用户身上并且包括来自多个源的信号。 该系统从广告商接收包括营销意图的输入。 该系统包括从用户数据和输入中提取的特征。 系统基于提取的特征获得每个用户的得分。 系统根据获得的分数从用户组中选择用户。

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