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    • 3. 发明申请
    • AUTOMATICALLY TRIGGERING PREDICTIONS IN RECOMMENDATION SYSTEMS BASED ON AN ACTIVITY-PROBABILITY THRESHOLD
    • 基于活动可靠性阈值的建议系统自动触发预测
    • US20130218825A1
    • 2013-08-22
    • US13402751
    • 2012-02-22
    • Rui ZhangKurt E. PartridgeRobert R. PriceJames M.A. BegoleMaurice K. Chu
    • Rui ZhangKurt E. PartridgeRobert R. PriceJames M.A. BegoleMaurice K. Chu
    • G06N7/02
    • G06Q10/04G06Q30/02
    • A recommender system determines a probability threshold for an activity-prediction model, and uses the probability threshold to predict whether a user is performing a target activity. To determine the probability threshold, the system computes a set of activity probabilities based on contextual information for a set of historical activities, and based on an activity-prediction model for a target activity. The system then compares a set of probability thresholds with the set of activity probabilities to determine a prediction success rate for each probability threshold. The system computes a utility score for each probability threshold based on the prediction success rates and a utility function, and selects a probability threshold whose utility score is optimal amongst the utility scores of the set of thresholds and greater than or equal to a baseline utility score. The system then assigns the probability threshold to the activity-prediction model.
    • 推荐系统确定活动预测模型的概率阈值,并使用概率阈值来预测用户是否正在执行目标活动。 为了确定概率阈值,系统基于一组历史活动的上下文信息,并且基于目标活动的活动预测模型来计算一组活动概率。 然后,系统将一组概率阈值与活动概率集合进行比较,以确定每个概率阈值的预测成功率。 该系统基于预测成功率和效用函数来计算每个概率阈值的效用得分,并且选择一个概率阈值,其效用评分在阈值集合的效用评分之间是最佳的,并且大于或等于基准效用得分 。 系统然后将概率阈值分配给活动预测模型。
    • 4. 发明申请
    • SPATIAL ASSOCIATION BETWEEN VIRTUAL AND AUGMENTED REALITY
    • 虚拟和现实之间的空间关系
    • US20110316845A1
    • 2011-12-29
    • US12823939
    • 2010-06-25
    • Michael RobertsJames M.A. BegoleMaurice K. ChuDoron Kletter
    • Michael RobertsJames M.A. BegoleMaurice K. ChuDoron Kletter
    • G06T15/00G09G5/00
    • G06T19/006
    • One embodiment of the present invention provides a system that facilitates interaction between two entities located away from each other. The system includes a virtual reality system, an augmented reality system, and an object-state-maintaining mechanism. During operation, the virtual reality system displays an object associated with a real-world object. The augmented reality system displays the object based on a change to the state of the object. The object-state-maintaining mechanism determines the state of the object and communicates a state change to the virtual reality system, the augmented reality system, or both. A respective state change of the object can be based on one or more of: a state change of the real-world object; a user input to the virtual reality system or the augmented reality system; and an analysis of an image of the real-world object.
    • 本发明的一个实施例提供一种促进彼此远离的两个实体之间的相互作用的系统。 该系统包括虚拟现实系统,增强现实系统以及对象状态维护机制。 在操作期间,虚拟现实系统显示与真实世界对象相关联的对象。 增强现实系统基于对对象状态的改变显示对象。 对象状态维护机制确定对象的状态并将状态改变传达给虚拟现实系统,增强现实系统或两者。 对象的相应状态变化可以基于以下中的一个或多个:现实世界对象的状态变化; 用户输入到虚拟现实系统或增强现实系统; 以及对真实世界对象的图像的分析。
    • 5. 发明申请
    • SENSOR-INTEGRATED MIRROR FOR DETERMINING CONSUMER SHOPPING BEHAVIOR
    • 用于确定消费者购物行为的传感器集成镜
    • US20110112890A1
    • 2011-05-12
    • US12614922
    • 2009-11-09
    • Maurice K. ChuJames M.A. Begole
    • Maurice K. ChuJames M.A. Begole
    • G06Q30/00H04N7/18G06N5/02G06F15/18
    • G06Q30/02G06Q30/0204
    • A mirror system includes an image sensor coupled to a mirror, and gathers consumer shopping preferences for merchandise items. During operation, the system gathers one or more sequential images, from the image sensor, of a consumer wearing a first wearable merchandise item in front of the image sensor. Next, the system identifies in the one or more sequential images a first merchandise item being worn by the consumer. Then, the system determines a demographic group associated with the consumer, and detects behavior patterns for the consumer, wherein the behavior pattern indicates an interest level of the consumer for the identified merchandise item. The system then determines a mapping between the identified consumer demographic group and an interest level for the identified merchandise item, and produces a model which encodes the mapping.
    • 镜系统包括耦合到镜子的图像传感器,并且收集商品的消费者购物偏好。 在操作期间,系统从图像传感器收集穿过图像传感器前面的第一可穿戴商品的消费者的一个或多个顺序图像。 接下来,系统在一个或多个顺序图像中识别由消费者佩戴的第一商品。 然后,系统确定与消费者相关联的人口统计组,并且检测消费者的行为模式,其中行为模式指示消费者对所识别的商品项目的兴趣水平。 然后,系统确定所识别的消费者人口统计组与所识别的商品项目的兴趣水平之间的映射,并且产生对映射进行编码的模型。
    • 8. 发明申请
    • CONTEXTUALLY SPECIFIC OPPORTUNITY BASED ADVERTISING
    • 基于特定机会的广告
    • US20120130806A1
    • 2012-05-24
    • US12949666
    • 2010-11-18
    • Kurt E. PartridgeJames M.A. BegoleMaurice K. Chu
    • Kurt E. PartridgeJames M.A. BegoleMaurice K. Chu
    • G06Q30/00
    • G06Q30/0251
    • One embodiment of the present invention provides a system that facilitates contextually specific opportunity-based advertising. During operation, the system collects contextual information associated with a consumer, and determines a current activity and/or a future activity in which the consumer is engaged based on the contextual information. The system then predicts one or more upcoming advertisement opportunities associated with the consumer based on the determined activities, and presents the predicted opportunities to one or more advertisers, thereby allowing the advertisers to determine a bid amount for presenting an advertisement at the predicted opportunities. The system further selects at least one advertisement to present based on one or more of the following: the bid amount, the collected contextual information, an occurrence probability of the predicted advertisement opportunities, content of the advertisement, metadata associated with the advertisement; and presents the advertisement to the consumer.
    • 本发明的一个实施例提供一种促进基于上下文特定的基于机会的广告的系统。 在操作期间,系统收集与消费者相关联的上下文信息,并根据上下文信息确定消费者所参与的当前活动和/或未来活动。 然后,系统基于所确定的活动来预测与消费者相关联的一个或多个即将到来的广告机会,并将预测的机会呈现给一个或多个广告商,由此允许广告商确定用于在预测机会上呈现广告的出价金额。 该系统还基于以下一个或多个来选择至少一个广告来呈现:投标金额,收集的上下文信息,预测广告机会的发生概率,广告内容,与广告相关联的元数据; 并向消费者呈现广告。
    • 10. 发明授权
    • Automatically triggering predictions in recommendation systems based on an activity-probability threshold
    • 基于活动概率阈值自动触发推荐系统中的预测
    • US08732097B2
    • 2014-05-20
    • US13402751
    • 2012-02-22
    • Rui ZhangKurt E. PartridgeRobert R. PriceJames M. A. BegoleMaurice K. Chu
    • Rui ZhangKurt E. PartridgeRobert R. PriceJames M. A. BegoleMaurice K. Chu
    • G06F15/18
    • G06Q10/04G06Q30/02
    • A recommender system determines a probability threshold for an activity-prediction model, and uses the probability threshold to predict whether a user is performing a target activity. To determine the probability threshold, the system computes a set of activity probabilities based on contextual information for a set of historical activities, and based on an activity-prediction model for a target activity. The system then compares a set of probability thresholds with the set of activity probabilities to determine a prediction success rate for each probability threshold. The system computes a utility score for each probability threshold based on the prediction success rates and a utility function, and selects a probability threshold whose utility score is optimal amongst the utility scores of the set of thresholds and greater than or equal to a baseline utility score. The system then assigns the probability threshold to the activity-prediction model.
    • 推荐系统确定活动预测模型的概率阈值,并使用概率阈值来预测用户是否正在执行目标活动。 为了确定概率阈值,系统基于一组历史活动的上下文信息,并且基于目标活动的活动预测模型来计算一组活动概率。 然后,系统将一组概率阈值与活动概率集合进行比较,以确定每个概率阈值的预测成功率。 该系统基于预测成功率和效用函数来计算每个概率阈值的效用得分,并且选择一个概率阈值,其效用评分在阈值集合的效用评分之间是最佳的,并且大于或等于基准效用得分 。 系统然后将概率阈值分配给活动预测模型。