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1. 发明申请

US20120084859A1 REALTIME MULTIPLE ENGINE SELECTION AND COMBINING 有权
标题翻译：实时多发动机选择和组合
公开(公告)号：US20120084859A1
公开(公告)日：2012-04-05
申请号：US12894185
申请日：2010-09-30
申请人： Kira Radinsky , Roy Varshavsky , Jack W. Stokes , Vladimir Holostov , Edward Schaefer
发明人： Kira Radinsky , Roy Varshavsky , Jack W. Stokes , Vladimir Holostov , Edward Schaefer
IPC分类号： G06F21/00 , G06F17/30
CPC分类号： G06F21/563 , G06F21/56 , G06Q10/06 , G06Q30/00
摘要： Architecture that selects a classification engine based on the expertise of the engine to process a given entity (e.g., a file). Selection of an engine is based on a probability that the engine will detect an unknown entity classification using properties of the entity. One or more of the highest ranked engines are activated in order to achieve the desired performance. A statistical, performance-light module is employed to skip or select several performance-demanding processes. Methods and algorithms are utilized for learning based on matching the best classification engine(s) to detect the entity class based on the entity properties. A user selection option is provided for specifying a maximum number of ranked, classification engines to consider for each state of the machine. A user can also select the minimum probability of detection for a specific entity (e.g., unknown file). The best classifications are re-evaluated over time as the classification engines are updated.
摘要翻译：基于引擎的专长来选择分类引擎以处理给定实体（例如，文件）的架构。引擎的选择是基于引擎将使用实体的属性来检测未知实体分类的概率。一个或多个最高排名的引擎被激活以实现期望的性能。采用统计的性能灯模块来跳过或选择若干性能要求高的过程。基于匹配最佳分类引擎的方法和算法用于学习，以根据实体属性检测实体类。提供用户选择选项，用于指定针对机器的每个状态考虑的排名最大的分类引擎。用户还可以选择特定实体（例如，未知文件）的最小检测概率。随着分类引擎的更新，最好的分类会随着时间的推移重新评估。

2. 发明授权

US08869277B2 Realtime multiple engine selection and combining 有权
标题翻译：实时多引擎选择和组合
公开(公告)号：US08869277B2
公开(公告)日：2014-10-21
申请号：US12894185
申请日：2010-09-30
申请人： Kira Radinsky , Roy Varshavsky , Jack W. Stokes , Vladimir Holostov , Edward Schaefer
发明人： Kira Radinsky , Roy Varshavsky , Jack W. Stokes , Vladimir Holostov , Edward Schaefer
IPC分类号： G06F21/00 , G06Q30/00 , G06F21/56
CPC分类号： G06F21/563 , G06F21/56 , G06Q10/06 , G06Q30/00
摘要： Architecture that selects a classification engine based on the expertise of the engine to process a given entity (e.g., a file). Selection of an engine is based on a probability that the engine will detect an unknown entity classification using properties of the entity. One or more of the highest ranked engines are activated in order to achieve the desired performance. A statistical, performance-light module is employed to skip or select several performance-demanding processes. Methods and algorithms are utilized for learning based on matching the best classification engine(s) to detect the entity class based on the entity properties. A user selection option is provided for specifying a maximum number of ranked, classification engines to consider for each state of the machine. A user can also select the minimum probability of detection for a specific entity (e.g., unknown file). The best classifications are re-evaluated over time as the classification engines are updated.
摘要翻译：基于引擎的专长来选择分类引擎以处理给定实体（例如，文件）的架构。引擎的选择是基于引擎将使用实体的属性来检测未知实体分类的概率。一个或多个最高排名的引擎被激活以实现期望的性能。采用统计的性能灯模块来跳过或选择若干性能要求高的过程。基于匹配最佳分类引擎的方法和算法用于学习，以根据实体属性检测实体类。提供用户选择选项，用于指定针对机器的每个状态考虑的排名最大的分类引擎。用户还可以选择特定实体（例如，未知文件）的最小检测概率。随着分类引擎的更新，最好的分类会随着时间的推移重新评估。

3. 发明申请

US20120209920A1 SOCIAL INFLUENCERS DISCOVERY 审中-公开
标题翻译：社会影响发现
公开(公告)号：US20120209920A1
公开(公告)日：2012-08-16
申请号：US13042463
申请日：2011-03-08
申请人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Moshe Tennenholtz , Kira Radinsky , Roy Varshavsky
发明人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Moshe Tennenholtz , Kira Radinsky , Roy Varshavsky
IPC分类号： G06F17/30 , G06F15/16
CPC分类号： G06Q30/0201 , G06F16/9535
摘要： Social influencers may be identified for specific usage contexts and for influencer type. Influencers may be categorized by mavens, connectors, salesmen, or other categories. Within each usage context, a unified data model may be used to collect data from multiple sources, including multiple social networks, as well as to collect data from different levels of influencers in each usage context. The relevance of various communication media as well as the frequency and quality of use of the media may be factors used to determine a person's effectiveness as a specific type of influencer within a usage context.
摘要翻译：社会影响者可以针对具体使用情况和影响者类型进行识别。影响者可以通过商品，连接器，推销员或其他类别进行分类。在每个使用情况下，可以使用统一的数据模型来从多个来源（包括多个社交网络）收集数据，以及从每个使用环境中的不同级别的影响者收集数据。各种通信媒体的相关性以及媒体的频率和使用质量可以是用于在使用上下文中确定个人作为特定类型的影响者的有效性的因素。

4. 发明申请

US20120209674A1 SOCIAL MARKETING INCENTIVES AND REWARDS 审中-公开
标题翻译：社会营销激励和奖励
公开(公告)号：US20120209674A1
公开(公告)日：2012-08-16
申请号：US13041452
申请日：2011-03-07
申请人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Moshe Tennenholtz , Kira Radinsky , Roy Varshavsky
发明人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Moshe Tennenholtz , Kira Radinsky , Roy Varshavsky
IPC分类号： G06Q30/00
CPC分类号： G06Q30/0207 , G06Q50/01
摘要： A social marketing system may reward and incentivize participants, and may also have a fraud detection system. The manager may create social marketing campaigns that may be simulated to determine an expected set of activities, which may be compared to an actual set of activities. A fraud detection system may detect abnormal activity and may bring the activity to a manager's attention and may also punish the participants by withholding rewards, lowering the participant's reputation, or some other punishment mechanism.
摘要翻译：社会营销系统可以奖励和激励参与者，也可能有欺诈检测系统。经理可以创建可以模拟的社交营销活动，以确定预期的一组活动，这可以与一组实际的活动进行比较。欺诈检测系统可能会检测到异常活动，并可能引起经理注意的活动，也可以通过扣留奖励，降低参与者的声誉或其他惩罚机制来惩罚参与者。

5. 发明申请

US20120209832A1 SOCIAL NETWORK BASED CONTEXTUAL RANKING 有权
标题翻译：基于社会网络的上下文排名
公开(公告)号：US20120209832A1
公开(公告)日：2012-08-16
申请号：US13042460
申请日：2011-03-08
申请人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeld , Roy Varshavsky , Avigad Oron , Kira Radinsky
发明人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeld , Roy Varshavsky , Avigad Oron , Kira Radinsky
IPC分类号： G06F17/30 , G06F15/16
CPC分类号： G06F17/30867 , G06Q30/0282 , G06Q50/01
摘要： A ranked set of users may be calculated from an expertise categorization for each user and a person's trust in the users for specific categories. The ranked set of users may be used for presenting search results, recommendations, social marketing, or other uses. A person's reputation may be determined through various online activities. A person's trust in another person may be related to their proximity and activity in one or more social networks.
摘要翻译：可以根据每个用户的专业知识分类以及个人对特定类别的用户的信任来计算一组排名的用户。用户排名可能用于呈现搜索结果，建议，社交营销或其他用途。一个人的声誉可以通过各种在线活动来确定。一个人对另一个人的信任可能与一个或多个社交网络中的邻近度和活动有关。

6. 发明授权

US09870424B2 Social network based contextual ranking 有权
公开(公告)号：US09870424B2
公开(公告)日：2018-01-16
申请号：US13042460
申请日：2011-03-08
申请人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Roy Varshavsky , Avigad Oron , Kira Radinsky
发明人： Eugene (John) Neystadt , Ron Karidi , Yitzhak Tzahi Weisfeild , Roy Varshavsky , Avigad Oron , Kira Radinsky
IPC分类号： G06Q30/02 , G06Q10/10 , G06F17/30 , G06Q50/00
CPC分类号： G06F17/30867 , G06Q30/0282 , G06Q50/01
摘要： A ranked set of users may be calculated from an expertise categorization for each user and a person's trust in the users for specific categories. The ranked set of users may be used for presenting search results, recommendations, social marketing, or other uses. A person's reputation may be determined through various online activities. A person's trust in another person may be related to their proximity and activity in one or more social networks.

7. 发明申请

US20120158477A1 SOCIAL INCENTIVES PLATFORM 审中-公开
标题翻译：社会激励平台
公开(公告)号：US20120158477A1
公开(公告)日：2012-06-21
申请号：US12970968
申请日：2010-12-17
申请人： Moshe Tennenholtz , Roy Varshavsky , Ron Karidi , Aviv Zohar , Yuval Emek , Kira Radinsky
发明人： Moshe Tennenholtz , Roy Varshavsky , Ron Karidi , Aviv Zohar , Yuval Emek , Kira Radinsky
IPC分类号： G06Q30/00
CPC分类号： G06Q30/0217 , G06Q30/0214 , G06Q50/01
摘要： A social incentive system is described herein that formalizes information propagation through social networks in a structured and systematic way. The system provides incentives and rewards to entities who participate in propagating the information, allowing heavy influencers to gain from their influence while the marketer rewards them. The system provides one or more tools for creation and design of social incentive plans with rewards for socially distributing information, including marketing campaigns. In particular, the system introduces a semantic framework where marketers can create structured incentive plans for rewarding consumers and distribution platforms for distributing information through social networks. As users complete specified activities they earn points, and the points can be redeemed for various incentives, such as cash, debit cards, prizes, merchandise, subscriptions, and so forth. The framework is robustly designed to avoid abuse and allow for fraud detection.
摘要翻译：本文描述了一种社会激励制度，其通过社会网络以组织和系统的方式形式化信息传播。该系统为参与传播信息的实体提供激励和奖励，让重度影响者从营销人员的奖励中获益。该系统提供一个或多个工具，用于创建和设计社会激励计划，并提供社会分发信息（包括营销活动）的奖励。特别是，系统引入了一个语义框架，营销人员可以创建结构化的激励计划，以奖励消费者和通过社交网络分发信息的分发平台。当用户完成指定的活动时，他们可以获得积分，积分可以兑换现金，借记卡，奖品，商品，订阅等各种奖励。该框架设计强大，以避免滥用并允许欺诈检测。

8. 发明授权

US08166104B2 Client-centered usage classification 有权
标题翻译：以客户为中心的使用分类
公开(公告)号：US08166104B2
公开(公告)日：2012-04-24
申请号：US12406964
申请日：2009-03-19
申请人： Barak Shein , Kfir Karmon , Eran Yariv , Roy Varshavsky
发明人： Barak Shein , Kfir Karmon , Eran Yariv , Roy Varshavsky
IPC分类号： G06F15/16 , G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0251 , G06Q30/0255
摘要： User input actions from one or more user input devices can be received, and unfiltered user input information about the user input actions can be collected at a client computing environment. The unfiltered user input information can be filtered to produce filtered user input information. The filtered user input information can exclude personal information and include non-personal information. In addition, a user profile can be created using the filtered user input information.
摘要翻译：可以接收来自一个或多个用户输入设备的用户输入动作，并且可以在客户端计算环境中收集关于用户输入动作的未过滤的用户输入信息。可以对未过滤的用户输入信息进行过滤以产生过滤的用户输入信息。过滤的用户输入信息可以排除个人信息并包括非个人信息。此外，可以使用过滤的用户输入信息来创建用户简档。

9. 发明申请

US20110010366A1 HYBRID RECOMMENDATION SYSTEM 有权
标题翻译：混合推荐系统
公开(公告)号：US20110010366A1
公开(公告)日：2011-01-13
申请号：US12500657
申请日：2009-07-10
申请人： Roy Varshavsky , Moshe Tennenholtz , Ron Karidi
发明人： Roy Varshavsky , Moshe Tennenholtz , Ron Karidi
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06Q30/02
摘要： A recommendation system may use a network of relationships between many different entities to find search results and establish a relevance value for the search results. The relevance value may be calculated by analyzing trust and similarity components of each relationship between the search user and the entity providing the search results. The entities may be, for example, persons associated within express or implied social networks, or corporations or other organizations with a historical or other reputation. The relationships may be created through many different contact mechanisms and may be unidirectional, asymmetric bidirectional, or symmetric bidirectional relationships. The relationships may be different based on topic or other factors.
摘要翻译：推荐系统可以使用许多不同实体之间的关系网络来查找搜索结果并建立搜索结果的相关性值。可以通过分析搜索用户和提供搜索结果的实体之间的每个关系的信任和相似性分量来计算相关性值。实体可以是例如在明示或暗示的社交网络内的人，或具有历史或其他声誉的公司或其他组织。可以通过许多不同的接触机制来创建关系，并且可以是单向的，不对称的双向的或对称的双向关系。基于主题或其他因素，关系可能不同。

10. 发明申请

US20100169331A1 ONLINE RELEVANCE ENGINE 有权
标题翻译：在线相关引擎
公开(公告)号：US20100169331A1
公开(公告)日：2010-07-01
申请号：US12344812
申请日：2008-12-29
申请人： Ron Karidi , Roy Varshavsky , Noga Amit , Oded Elyada , Daniel Sitton , Limor Lahiani , Hen Fitoussi , Eran Yariv , Benny Schlesinger
发明人： Ron Karidi , Roy Varshavsky , Noga Amit , Oded Elyada , Daniel Sitton , Limor Lahiani , Hen Fitoussi , Eran Yariv , Benny Schlesinger
IPC分类号： G06F7/06 , G06F17/30 , G06F7/00
CPC分类号： G06F17/30864
摘要： Information is automatically located which is relevant to source content that a user is viewing on a user interface without requiring the user to perform an additional search or navigate links of the source content. The source content can be, e.g., a web page or a document from a word processing or email application. The relevant information can include images, videos, web pages, maps or other location-based information, people-based information and special services which aggregate different types of information. Related content is located by analyzing textual content, user behavior and connectivity relative to the source. The related content is scored for similarity to the source. Content which is sufficiently similar but not too similar is selected. Similar related content is grouped to select representative results. The selected content is filtering in multiple stages based on attribute priorities to avoid unnecessary processing of content which is filtered out an early stage.
摘要翻译：自动定位与用户正在用户界面上观看的源内容相关的信息，而不需要用户执行附加搜索或浏览源内容的链接。源内容可以是例如网页或来自文字处理或电子邮件应用的文档。相关信息可以包括图像，视频，网页，地图或其他基于位置的信息，基于人群的信息和聚合不同类型信息的特殊服务。通过分析文本内容，用户行为和相对于源的连接来定位相关内容。相关内容的得分与来源相似。选择足够相似但不太相似的内容。类似的相关内容被分组以选择代表性的结果。所选择的内容是基于属性优先级在多个阶段进行过滤，以避免对早期过滤掉的内容进行不必要的处理。

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