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    • 1. 发明申请
    • DETECTING INAPPROPRIATE ACTIVITY BY ANALYSIS OF USER INTERACTIONS
    • 通过用户互动分析检测不准确的活动
    • US20080162202A1
    • 2008-07-03
    • US11618309
    • 2006-12-29
    • Richendra KhannaEugene KalenkovichRajiv Chopra
    • Richendra KhannaEugene KalenkovichRajiv Chopra
    • G06Q99/00G06Q20/00
    • G06Q30/06G06Q20/10G06Q30/0248
    • Techniques are described for detecting inappropriate activities based on interactions with Web sites and other electronic information services. In some situations, the techniques involve analyzing user interactions with an electronic information service in order to determine whether the user interactions are likely to reflect fraudulent activities by the user. In at least some situations, information about user interactions may be analyzed by applying one or more assessment tests that are each configured to assess one or more aspects of the interactions and to provide indications of whether those interaction aspects reflect inappropriate activities. If an analysis of one or more user interactions determines that a user is suspected of inappropriate activity, various actions may be taken to inhibit the inappropriate activity from continuing or recurring in the future.
    • 描述了基于与网站和其他电子信息服务的交互来检测不适当活动的技术。 在某些情况下,这些技术涉及分析与电子信息服务的用户交互,以便确定用户交互是否可能反映用户的欺诈活动。 在至少一些情况下,可以通过应用一个或多个评估测试来分析关于用户交互的信息,所述评估测试被配置为评估交互的一个或多个方面,并且提供这些交互方面是否反映不当活动的指示。 如果对一个或多个用户交互的分析确定用户被怀疑是不适当的活动,则可以采取各种措施来阻止不必要的活动在将来继续或重复发生。
    • 5. 发明授权
    • Visually distinguishing portions of content
    • 目视区分内容的一部分
    • US08887044B1
    • 2014-11-11
    • US13535002
    • 2012-06-27
    • Joshua M. GoodspeedEugene KalenkovichTom Killalea
    • Joshua M. GoodspeedEugene KalenkovichTom Killalea
    • G06F3/00G06F3/048G06F17/00G06F3/0483G06F17/21
    • G06F3/0483G06F3/04842G06F17/212
    • In some implementations, a user may select a category, attribute or term related to content item. During presentation of the content item, an electronic device may visually distinguish (or, alternatively, hide) at least one portion of content associated with the selected category, attribute or term. In some examples, a user interface may be displayed to enable the user to select one or more categories, attributes, or terms related to the content item. The user interface may further enable the user to select a graphics scheme to be used for visually distinguishing at least one portion of content corresponding to the selection. Selection information identifying a portion of content to be visually distinguished or hidden may be sent to a content provider, such as for synchronization with other instances of the content item on other devices of a user, or for aggregation of the selection information by the content provider.
    • 在一些实现中,用户可以选择与内容项相关的类别,属性或术语。 在呈现内容项目期间,电子设备可以在视觉上区分(或替代地,隐藏)与所选择的类别,属性或术语相关联的内容的至少一部分。 在一些示例中,可以显示用户界面以使得用户能够选择与内容项相关的一个或多个类别,属性或术语。 用户界面还可以使用户能够选择要用于视觉区分对应于选择的内容的至少一部分的图形方案。 识别要视觉辨别或隐藏的内容的一部分的选择信息可以被发送到内容提供商,例如用于与用户的其他设备上的内容项的其他实例同步,或者由内容提供商聚合选择信息 。
    • 8. 发明授权
    • Person to person similarities based on media experiences
    • 基于媒体经验的人与人之间的相似之处
    • US08301692B1
    • 2012-10-30
    • US12485700
    • 2009-06-16
    • Janna HamakerEugene KalenkovichZaur KambarovTom Killalea
    • Janna HamakerEugene KalenkovichZaur KambarovTom Killalea
    • G06F15/16
    • G06Q30/0631
    • Similarities are discovered among different users with respect to their media experiences and other behaviors, such as taste in media items (e.g., books, music, movies, magazines, art, etc.), browsing behavior, purchase decisions, and online shopping habits, and usage history. The similarities are determined in part by substantially real-time comparison of individual users with a set of predetermined user-based clusters formed from the experiences and behaviors of sample users. Users from a population may then be identified based on similarity metrics. Recommendations for new media items, or other goods/services, may also be made based on choices being made by similar users.
    • 在媒体经验和其他行为(例如媒体项目(例如书籍,音乐,电影,杂志,艺术品等)中的品味),浏览行为,购买决定和在线购物习惯方面,在不同用户之间发现相似之处, 和使用历史。 这些相似性部分地通过基本上实时比较个体用户与由样本用户的经验和行为形成的一组预定的基于用户的集群来确定。 然后可以基于相似性度量来识别来自群体的用户。 对新媒体项目或其他商品/服务的建议也可以根据类似用户的选择进行。