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1. 发明授权

US08019702B1 Supervised learning with multi-scale time intervals using a statistical classification model to classify unlabeled events 有权
标题翻译：使用统计分类模型对多标度时间间隔进行监督学习，对未标记的事件进行分类
公开(公告)号：US08019702B1
公开(公告)日：2011-09-13
申请号：US12248784
申请日：2008-10-09
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F11/00
CPC分类号： G06K9/00523
摘要： A method, a system and a computer program product generate a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event.
摘要翻译：方法，系统和计算机程序产品生成计算机系统使用的统计分类模型来确定与未标记的时间序列事件相关联的类别。

2. 发明授权

US08140451B1 Supervised learning using multi-scale features from time series events and scale space decompositions 有权
标题翻译：使用时间序列事件和尺度空间分解的多尺度特征进行监督学习
公开(公告)号：US08140451B1
公开(公告)日：2012-03-20
申请号：US13183375
申请日：2011-07-14
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F11/00
CPC分类号： G06K9/00536 , G06K9/00516
摘要： Disclosed herein is a method, a system and a computer program product for generating a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event. Initially, a set of labeled time series events is received. A set of time series features is identified for a selected set of the labeled time series events. A plurality of scale space decompositions is generated based on the set of time series features. A plurality of multi-scale features is generated based on the plurality of scale space decompositions. A first subset of the plurality of multi-scale features that correspond at least in part to a subset of space or time points within a time series event that contain feature data that distinguish the time series event as belonging to a class of time series events that corresponds to the class label are identified. A statistical classification model for classifying an unlabeled time series event based on the class corresponding with the class label is generated based at least in part on the at the first subset of the plurality of multi-scale features.
摘要翻译：本文公开了一种用于生成由计算机系统用于确定与未标记的时间序列事件相关联的类别的统计分类模型的方法，系统和计算机程序产品。最初，接收一组标记的时间序列事件。针对所选择的一组标记的时间序列事件识别一组时间序列特征。基于该组时间序列特征生成多个比例空间分解。基于多个刻度空间分解产生多个多尺度特征。所述多个多尺度特征的第一子集至少部分对应于时间序列事件内的空间或时间点的子集，所述时间序列事件包含将所述时间序列事件区分为属于一类时间序列事件的特征数据，所述时间序列事件对应于类标签被识别。至少部分地基于多个多尺度特征的第一子集来生成用于基于与类标签相对应的类来分类未标记时间序列事件的统计分类模型。

3. 发明授权

US08001062B1 Supervised learning using multi-scale features from time series events and scale space decompositions 有权
标题翻译：使用时间序列事件和尺度空间分解的多尺度特征进行监督学习
公开(公告)号：US08001062B1
公开(公告)日：2011-08-16
申请号：US11952436
申请日：2007-12-07
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F11/00
CPC分类号： G06K9/00536 , G06K9/00516
摘要： Disclosed herein is a method, a system and a computer program product for generating a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event. Initially, a set of labeled time series events is received. A set of time series features is identified for a selected set of the labeled time series events. A plurality of scale space decompositions is generated based on the set of time series features. A plurality of multi-scale features is generated based on the plurality of scale space decompositions. A first subset of the plurality of multi-scale features that correspond at least in part to a subset of space or time points within a time series event that contain feature data that distinguish the time series event as belonging to a class of time series events that corresponds to the class label are identified. A statistical classification model for classifying an unlabeled time series event based on the class corresponding with the class label is generated based at least in part on the at the first subset of the plurality of multi-scale features.
摘要翻译：本文公开了一种用于生成由计算机系统用于确定与未标记的时间序列事件相关联的类别的统计分类模型的方法，系统和计算机程序产品。最初，接收一组标记的时间序列事件。针对所选择的一组标记的时间序列事件识别一组时间序列特征。基于该组时间序列特征生成多个比例空间分解。基于多个刻度空间分解产生多个多尺度特征。所述多个多尺度特征的第一子集至少部分对应于时间序列事件内的空间或时间点的子集，所述时间序列事件包含将所述时间序列事件区分为属于一类时间序列事件的特征数据，所述时间序列事件对应于类标签被识别。至少部分地基于多个多尺度特征的第一子集来生成用于基于与类标签相对应的类来分类未标记时间序列事件的统计分类模型。

4. 发明授权

US08683521B1 Feature-based video suggestions 有权
标题翻译：基于功能的视频建议
公开(公告)号：US08683521B1
公开(公告)日：2014-03-25
申请号：US12415923
申请日：2009-03-31
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F13/00
CPC分类号： H04N21/251 , H04N21/4826
摘要： A suggestion server generates suggestions of videos. The suggestion server analyzes log data to create co-watch data identifying pairs of co-watched videos and containing generate values representing the number of times the pairs of videos were co-watched. The suggestion server uses the co-watch data to create feature vectors for the co-watched videos. The suggestion server uses the feature vectors to train a ranker for each video. When trained, the ranker can be applied to a feature vector for a video to produce a ranking score. To produce suggestions for a given video, a set of candidate videos is defined. The suggestion server applies the feature vectors for the candidates to the ranker for the given video to produce ranking scores. The candidate videos are ranked based on their ranking scores, and the highest-ranked candidates are provided as suggestions for the given video.
摘要翻译：建议服务器生成视频的建议。建议服务器分析日志数据以创建识别共同观看视频对的共观察数据，并且包含表示视频对被共同观看的次数的生成值。建议服务器使用共同观察数据为共同观看的视频创建特征向量。建议服务器使用特征向量为每个视频训练游戏者。经过训练后，游戏者可以应用于视频的特征向量以产生排名得分。为了产生给定视频的建议，定义了一组候选视频。建议服务器将候选人的特征向量应用于给定视频的游侠以产生排名得分。候选视频根据其排名分数进行排名，排名最高的候选人被提供给给定视频的建议。

5. 发明授权

US08510252B1 Classification of inappropriate video content using multi-scale features 有权
标题翻译：使用多尺度功能对不适当的视频内容进行分类
公开(公告)号：US08510252B1
公开(公告)日：2013-08-13
申请号：US12248780
申请日：2008-10-09
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F9/44 , G06N7/02 , G06N7/06
CPC分类号： G06K9/00523
摘要： A method, a system and a computer program product generate a statistical classification model used by a computer system to determine whether a video contains content in a particular class, such as inappropriate content.
摘要翻译：方法，系统和计算机程序产品产生计算机系统使用的统计分类模型，以确定视频是否包含特定类中的内容，例如不适当的内容。

6. 发明授权

US08209270B2 Supervised learning with multi-scale time intervals using a statistical classification model to classify unlabeled events 有权
标题翻译：使用统计分类模型对多标度时间间隔进行监督学习，对未标记的事件进行分类
公开(公告)号：US08209270B2
公开(公告)日：2012-06-26
申请号：US13195755
申请日：2011-08-01
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F11/00
CPC分类号： G06K9/00523
摘要： A method, a system and a computer program product generate a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event.
摘要翻译：方法，系统和计算机程序产品生成计算机系统使用的统计分类模型来确定与未标记的时间序列事件相关联的类别。

7. 发明申请

US20110289033A1 Supervised Learning with Multi-Scale Time Intervals Using a Statistical Classification Model to Classify Unlabeled Events 有权
标题翻译：使用统计分类模型对未标记事件进行分类的多尺度时间间隔的监督学习
公开(公告)号：US20110289033A1
公开(公告)日：2011-11-24
申请号：US13195755
申请日：2011-08-01
申请人： Ullas Gargi , Jay Yagnik
发明人： Ullas Gargi , Jay Yagnik
IPC分类号： G06F15/18
CPC分类号： G06K9/00523
摘要： A method, a system and a computer program product generate a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event.
摘要翻译：方法，系统和计算机程序产品生成计算机系统使用的统计分类模型来确定与未标记的时间序列事件相关联的类别。

8. 发明授权

US08959540B1 Predicting engagement in video content 有权
标题翻译：预测参与视频内容
公开(公告)号：US08959540B1
公开(公告)日：2015-02-17
申请号：US12783524
申请日：2010-05-19
申请人： Ullas Gargi , Jay Yagnik , Anindya Sarkar
发明人： Ullas Gargi , Jay Yagnik , Anindya Sarkar
IPC分类号： H04N7/16 , H04H60/32
CPC分类号： H04N21/23418 , H04H20/93 , H04H60/31 , H04H60/46 , H04H60/59 , H04H60/63 , H04N21/237 , H04N21/251 , H04N21/25891 , H04N21/44008 , H04N21/44222 , H04N21/466 , H04N21/4826 , H04N21/6582
摘要： User engagement in unwatched videos is predicted by collecting and aggregating data describing user engagement with watched videos. The data are normalized to reduce the influence of factors other than the content of the videos on user engagement. Engagement metrics are calculated for segments of watched videos that indicate user engagement with each segment relative to overall user engagement with the watched videos. Features of the watched videos within time windows are characterized, and a function is learned that relates the features of the videos within the time windows to the engagement metrics for the time windows. The features of a time window of an unwatched video are characterized, and the learned function is applied to the features to predict user engagement to the time window of the unwatched video. The unwatched video can be enhanced based on the predicted user engagement.
摘要翻译：通过收集和汇总描述与观看视频的用户互动的数据来预测用户对未拍摄的视频的参与。数据被归一化以减少视频内容以外的因素对用户参与的影响。针对所观看视频的细分，计算参与指标，指示用户与每个细分受众群相对于与观看视频的整体用户互动度的参与度。在时间窗口中观看视频的特征被描述，并且学习了将时间窗口内的视频的特征与时间窗口的参与度量相关联的功能。对未拍摄视频的时间窗口的特征进行了表征，并且将学习的功能应用于特征以预测用户对未拍摄视频的时间窗口的参与。可以根据预测的用户参与来增强未拍摄的视频。

9. 发明授权

US08756677B2 Variable-strength security based on time and/or number of partial password unlocks 有权
标题翻译：基于部分密码解锁的时间和/或数量的可变强度安全性
公开(公告)号：US08756677B2
公开(公告)日：2014-06-17
申请号：US13483310
申请日：2012-05-30
申请人： Ullas Gargi
发明人： Ullas Gargi
IPC分类号： G06F21/00
CPC分类号： G06F21/31
摘要： An authentication scheme for unlocking a computing system may require a shortened password in some cases. For example, the computing system may be configured to determine a time that a user has been locked out of a computing device and to determine which of a plurality of time spans that the time falls within. The computing system may also prompt the user for a required password including a full password or a subset of the full password depending on the determined time span. The computing system may be further configured to display a visual indicator corresponding to the determined time span or a required password length on a visual display. A length of the required password for login may be progressively longer for each of the plurality of time spans as a time period that a respective time span covers increases.
摘要翻译：用于解锁计算系统的认证方案在某些情况下可能需要缩短密码。例如，计算系统可以被配置为确定用户已被锁定在计算设备之外的时间并且确定时间落在其中的多个时间跨度中的哪一个。计算系统还可以根据确定的时间间隔来提示用户所需的密码，包括完整密码或全密码的子集。计算系统还可以被配置为在视觉显示器上显示对应于所确定的时间跨度的视觉指示符或所需的密码长度。对于多个时间跨度中的每一个，对于相应时间范围覆盖的时间段增加，登录所需的密码的长度可以逐渐变长。

10. 发明授权

US08725113B2 User proximity control of devices 有权
标题翻译：设备的用户接近控制
公开(公告)号：US08725113B2
公开(公告)日：2014-05-13
申请号：US13417818
申请日：2012-03-12
申请人： Ullas Gargi , Rich Gossweiler
发明人： Ullas Gargi , Rich Gossweiler
IPC分类号： H04M1/66
CPC分类号： H04M1/67 , G06F21/35 , G06F21/74 , G06F2221/2111 , H04M1/7253 , H04M2250/02 , H04W12/08 , H04W88/02
摘要： Examples of embodiments provide systems and methods for varying the functions of an electronic device according to a physical relationship (e.g. the distance) between the electronic device and the primary user (e.g., owner) of the electronic device. The device may measure the distance using a wireless signal from a secondary device carried by or associated with the primary user. In some embodiments, the electronic device may change its functions based on its environment, in combination with the distance between the electronic device and the primary user. Environmental factors may include the device's location, the device's velocity, and the date and time of day.
摘要翻译：实施例的示例提供了根据电子设备和电子设备的主要用户（例如，所有者）之间的物理关系（例如距离）来改变电子设备的功能的系统和方法。设备可以使用来自与主用户携带或关联的辅助设备的无线信号来测量距离。在一些实施例中，电子设备可以基于其环境，结合电子设备和主用户之间的距离来改变其功能。环境因素可能包括设备的位置，设备的速度以及日期和时间。

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