公开(公告)号：US09519682B1

公开(公告)日：2016-12-13

申请号：US13117037

申请日：2011-05-26

申请人： Jay Pujara ,  Vishwanath Tumkur Ramarao ,  Xiaopeng Xi ,  Martin Zinkevich ,  Anirban Dasgupta ,  Belle Tseng ,  Wei Chu ,  Jyh-Shin Gareth Shue

发明人： Jay Pujara ,  Vishwanath Tumkur Ramarao ,  Xiaopeng Xi ,  Martin Zinkevich ,  Anirban Dasgupta ,  Belle Tseng ,  Wei Chu ,  Jyh-Shin Gareth Shue

IPC分类号： G06F11/00 ,  G06F17/30 ,  G06Q10/10 ,  H04H20/28 ,  H04H60/82 ,  G06F12/14

CPC分类号： G06F17/3053 ,  G06Q10/10 ,  H04H20/28 ,  H04H60/82

摘要： Embodiments are directed towards generating a unified user account trustworthiness system through user account trustworthiness scores. A trusted group of user accounts may be identified for a given action by grouping a plurality of user accounts into tiers based on a trustworthiness score of each user account for the given action. The tiers and/or trustworthiness scores may be employed to classify an item, such as a message as spam or non-spam, based on input from the user accounts. The trustworthiness scores may also be employed to determine if a user account is a robot account or a human account. The trusted group for a given action may dynamically evolve over time by regrouping the user accounts based on modified trustworthiness scores. A trustworthiness score of an individual user account may be modified based on input received from the individual user account and input from other user accounts.

摘要翻译： 实施例旨在通过用户帐户可信度得分来生成统一的用户帐户可信赖性系统。 可以基于针对给定动作的每个用户帐户的可信度分数将多个用户帐户分组成层，可以为给定动作识别可信赖的用户帐户组。 层级和/或可信赖性分数可以用于基于来自用户帐户的输入来将项目（诸如作为垃圾邮件或非垃圾邮件）的消息分类。 还可以使用可信度分数来确定用户帐户是机器人帐户还是人类账户。 给定动作的受信任组可以通过基于修改的可信度得分重新分组用户账户而随着时间的推移而动态演变。 可以基于从单个用户帐户接收的输入和来自其他用户帐户的输入来修改个人用户帐户的可信度分数。

公开(公告)号：US08301719B2

公开(公告)日：2012-10-30

申请号：US12963514

申请日：2010-12-08

申请人： Ke Wei ,  Hao Zheng ,  Jay Pujara

发明人： Ke Wei ,  Hao Zheng ,  Jay Pujara

IPC分类号： G06F15/16 ,  G06K9/00

CPC分类号： G06T7/44 ,  H04L51/12

摘要： A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.

摘要翻译： 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样，则可以将图像转换成灰度图像，然后执行边缘检测，然后消除弱边缘的非最大值和阈值。 边缘像素，然后用于确定归一化像素密度分布（PDD）。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈，基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。

公开(公告)号：US20090043853A1

公开(公告)日：2009-02-12

申请号：US11834529

申请日：2007-08-06

申请人： Ke Wei ,  Hao Zheng ,  Jay Pujara

发明人： Ke Wei ,  Hao Zheng ,  Jay Pujara

IPC分类号： G06F15/16

CPC分类号： G06T7/44 ,  H04L51/12

摘要： A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.

摘要翻译： 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样，则可以将图像转换成灰度图像，然后执行边缘检测，然后消除弱边缘的非最大值和阈值。 边缘像素，然后用于确定归一化像素密度分布（PDD）。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈，基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。

公开(公告)号：US20080300972A1

公开(公告)日：2008-12-04

申请号：US11755571

申请日：2007-05-30

申请人： Jay Pujara

发明人： Jay Pujara

IPC分类号： G06Q30/00

CPC分类号： G06Q30/02 ,  G06Q30/0257 ,  G06Q30/0263 ,  G06Q30/0277

摘要： Systems and methods for incorporating user feedback on advertising relevancy and providing the feedback to advertisers is disclosed. Generally, a user requests a web page from an online service provider. The online service provider checks to determine if the user requesting the page is a member of the user assisted advertising relevancy user population. If the user is not a member, the online service provider sends the web page the user requested without a method to rate the advertisement. If the user is a member of the user assisted advertising relevancy user base, the online service provider sends the requested web page with the ability to rate the advertisements sent on the page.

摘要翻译： 公开了将用户对广告相关性的反馈和向广告商提供反馈的系统和方法。 通常，用户从在线服务提供商请求网页。 在线服务提供商检查以确定请求页面的用户是否是用户辅助广告相关用户群体的成员。 如果用户不是成员，则在线服务提供者发送用户请求的网页，而不用对广告进行评估。 如果用户是用户辅助广告相关用户群的成员，则在线服务提供商发送所请求的网页以对在页面上发送的广告进行评级的能力。

公开(公告)号：US08069128B2

公开(公告)日：2011-11-29

申请号：US12188612

申请日：2008-08-08

申请人： Jay Pujara

发明人： Jay Pujara

IPC分类号： G06F17/00 ,  G06N5/02

CPC分类号： H04L51/12 ,  G06Q10/107

摘要： Embodiments are directed towards employing a multi-pass ad-hoc spam message filtering approach that dynamically generates a temporary classifier during a first pass based on a result of a previously applied message filter that sorts messages into various folders for a user. The first pass scans messages in a user's mail folders, and reads various information within the messages, including, but not limited to sender information, headers, including a subject, an originating network address, message contents, attachments, and the like. After creating a classification model, the classifier with its model is used in a second pass on the message folders to retrospectively inspect the messages and present to the user a list of messages that might be misclassified. The classification model is maintained within memory on a user's client device, as memory resident only, and is not stored on disk or within another persistent data store.

摘要翻译： 实施例旨在采用基于先前应用的消息过滤器的动态生成临时分类器的多遍自组织垃圾邮件过滤方法，该消息过滤器将消息分类成用户的各种文件夹。 第一遍扫描用户的邮件文件夹中的邮件，并且读取消息内的各种信息，包括但不限于发件人信息，包括主题的标题，发起网络地址，消息内容，附件等。 在创建分类模型之后，使用其模型的分类器在消息文件夹的第二遍中使用，以回顾性地检查消息，并向用户呈现可能被错误分类的消息列表。 分类模型在用户的客户端设备的内存中维护，仅作为内存驻留，并且不存储在磁盘上或另一个持久数据存储中。

公开(公告)号：US07849146B2

公开(公告)日：2010-12-07

申请号：US12035371

申请日：2008-02-21

申请人： Jaesik Choi ,  Jay Pujara ,  Vishwanth Tumkur Ramarao ,  Ke Wei

发明人： Jaesik Choi ,  Jay Pujara ,  Vishwanth Tumkur Ramarao ,  Ke Wei

IPC分类号： G06F15/16

CPC分类号： H04L51/12

摘要： Detecting and blocking spam messages using statistical analysis on distributions of message sizes for a given IP address. Mail volumes are examined to model a distribution of volumes to cluster IP addresses. The messages sizes may distributed across ranges of message sizes, which is then used to determine an entropy of message sizes for the given IP address. The entropy of the given IP address may be compared to entropies of known good IP addresses, and if a difference between the entropies is statistically significant, then the given IP address may be determined to be an IP spammer. User feedback may also be employed to further characterize an IP address. For example, a number of messages from the IP address may be sent to intended recipients. User feedback may then be monitored to determine whether to the IP address should be reclassified.

摘要翻译： 使用对给定IP地址的邮件大小分布的统计分析来检测和阻止垃圾邮件。 检查邮件卷以将卷的分布建模为群集IP地址。 消息大小可以分布在消息大小的范围内，然后用于确定给定IP地址的消息大小的熵。 可以将给定IP地址的熵与已知良好IP地址的熵进行比较，并且如果熵之间的差异具有统计学意义，则给定的IP地址可被确定为IP垃圾邮件发送者。 还可以使用用户反馈来进一步表征IP地址。 例如，可以将来自IP地址的多个消息发送到预期的接收者。 然后可以监视用户反馈，以确定IP地址是否应重新分类。

公开(公告)号：US20100036786A1

公开(公告)日：2010-02-11

申请号：US12188612

申请日：2008-08-08

申请人： Jay Pujara

发明人： Jay Pujara

IPC分类号： G06N5/02 ,  G06F15/16

CPC分类号： H04L51/12 ,  G06Q10/107

摘要： Embodiments are directed towards employing a multi-pass ad-hoc spam message filtering approach that dynamically generates a temporary classifier during a first pass based on a result of a previously applied message filter that sorts messages into various folders for a user. The first pass scans messages in a user's mail folders, and reads various information within the messages, including, but not limited to sender information, headers, including a subject, an originating network address, message contents, attachments, and the like. After creating a classification model, the classifier with its model is used in a second pass on the message folders to retrospectively inspect the messages and present to the user a list of messages that might be misclassified. The classification model is maintained within memory on a user's client device, as memory resident only, and is not stored on disk or within another persistent data store.

摘要翻译： 实施例旨在采用基于先前应用的消息过滤器的动态生成临时分类器的多遍自组织垃圾邮件过滤方法，该消息过滤器将消息分类成用户的各种文件夹。 第一遍扫描用户的邮件文件夹中的邮件，并且读取消息内的各种信息，包括但不限于发件人信息，包括主题的标题，发起网络地址，消息内容，附件等。 在创建分类模型之后，使用其模型的分类器在消息文件夹的第二遍中使用，以回顾性地检查消息，并向用户呈现可能被错误分类的消息列表。 分类模型在用户的客户端设备的内存中维护，仅作为内存驻留，并且不存储在磁盘上或另一个持久数据存储中。

公开(公告)号：US20110078269A1

公开(公告)日：2011-03-31

申请号：US12963514

申请日：2010-12-08

申请人： Ke WEI ,  Hao Zheng ,  Jay Pujara

发明人： Ke WEI ,  Hao Zheng ,  Jay Pujara

IPC分类号： G06F15/16 ,  G06K9/00

CPC分类号： G06T7/44 ,  H04L51/12

摘要： A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.

摘要翻译： 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样，则可以将图像转换成灰度图像，然后执行边缘检测，然后消除弱边缘的非最大值和阈值。 边缘像素，然后用于确定归一化像素密度分布（PDD）。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈，基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。

公开(公告)号：US07882177B2

公开(公告)日：2011-02-01

申请号：US11834529

申请日：2007-08-06

申请人： Ke Wei ,  Hao Zheng ,  Jay Pujara

发明人： Ke Wei ,  Hao Zheng ,  Jay Pujara

IPC分类号： G06K9/60

CPC分类号： G06T7/44 ,  H04L51/12

摘要： A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.

摘要翻译： 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样，则可以将图像转换成灰度图像，然后执行边缘检测，然后消除弱边缘的非最大值和阈值。 边缘像素，然后用于确定归一化像素密度分布（PDD）。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈，基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。

公开(公告)号：US20090216841A1

公开(公告)日：2009-08-27

申请号：US12035371

申请日：2008-02-21

申请人： Jaesik Choi ,  Jay Pujara ,  Vishwanth Tumkur Ramarao ,  Ke Wei

发明人： Jaesik Choi ,  Jay Pujara ,  Vishwanth Tumkur Ramarao ,  Ke Wei

IPC分类号： G06F15/16

CPC分类号： H04L51/12

摘要： Detecting and blocking spam messages using statistical analysis on distributions of message sizes for a given IP address. Mail volumes are examined to model a distribution of volumes to cluster IP addresses. The messages sizes may distributed across ranges of message sizes, which is then used to determine an entropy of message sizes for the given IP address. The entropy of the given IP address may be compared to entropies of known good IP addresses, and if a difference between the entropies is statistically significant, then the given IP address may be determined to be an IP spammer. User feedback may also be employed to further characterize an IP address. For example, a number of messages from the IP address may be sent to intended recipients. User feedback may then be monitored to determine whether to the IP address should be reclassified.

摘要翻译： 使用对给定IP地址的邮件大小分布的统计分析来检测和阻止垃圾邮件。 检查邮件卷以将卷的分布建模为群集IP地址。 消息大小可以分布在消息大小的范围内，然后用于确定给定IP地址的消息大小的熵。 可以将给定IP地址的熵与已知良好IP地址的熵进行比较，并且如果熵之间的差异具有统计学意义，则给定的IP地址可被确定为IP垃圾邮件发送者。 还可以使用用户反馈来进一步表征IP地址。 例如，可以将来自IP地址的多个消息发送到预期的接收者。 然后可以监视用户反馈，以确定IP地址是否应重新分类。