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公开(公告)号：US20090271339A1
公开(公告)日：2009-10-29
申请号：US12111500
申请日：2008-04-29
IPC分类号： G06F15/18
CPC分类号： G06N20/00
摘要： Computer-implemented systems and methods, including servers, perform structure-based recognition processes that include matching and classification. Preprocessing subsystems and sub-methods embed a set of classes on which a loss function is defined into a semantic space and learn an input mapping between an input space and the semantic space. Recognition subsystems and methods accept a test object, representable in the input space, and apply the input mapping to the test object as part of a recognition process.
摘要翻译： 计算机实现的系统和方法，包括服务器，执行基于结构的识别过程，包括匹配和分类。 预处理子系统和子方法将一组将损失函数定义到一个语义空间中的类进行嵌入，并学习输入空间和语义空间之间的输入映射。 识别子系统和方法接受在输入空间中表示的测试对象，并将输入映射应用于测试对象作为识别过程的一部分。
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公开(公告)号：US20090327877A1
公开(公告)日：2009-12-31
申请号：US12164039
申请日：2008-06-28
IPC分类号： G06F17/27
CPC分类号： G06F17/2715 , G06F16/907 , G06F16/951
摘要： An improved system and method for disambiguating text strings labeling content objects is provided. A text string set may be received from a user. Frequencies of co-occurring text strings in a text collection may be obtained, and a disambiguation measure may be determined for a pair of text strings that each co-occur with a text string in the text string set. The disambiguation measure may be based on a weighted KL divergence of text string distributions that maximizes the value of divergence when a text string set may occur in different contexts. A disambiguation measure may be determined for a list of the top most common pairs of text strings that co-occur with the text string set, and the pairs of text strings may be output in decreasing order by disambiguation measure for those pairs of text strings with a disambiguation measure that exceeds a threshold.
摘要翻译： 提供了一种用于消除文本字符串标注内容对象的改进的系统和方法。 可以从用户接收文本串集。 可以获得文本集合中共同出现的文本字符串的频率，并且可以针对文本串集合中的文本字符串共同出现的一对文本字符串来确定消歧量度。 消歧措施可以基于文本串分布的加权KL散度，当文本串集合可能发生在不同的上下文中时，可以使发散的值最大化。 可以确定与文本串集合共同出现的最常见的文本串对的列表的消歧措施，并且可以通过对这些文本串的消歧量度量以递减的顺序输出文本串对， 超出阈值的消歧措施。
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公开(公告)号：US09639780B2
公开(公告)日：2017-05-02
申请号：US12341587
申请日：2008-12-22
IPC分类号： G06K9/62
CPC分类号： G06K9/6256
摘要： A system and method for improved classification. A first classifier is trained using a first process running on at least one computing device using a first set of training images relating to a class of images. A set of additional images are selected using the first classifier from a source of additional images accessible to the computing device. The first set of training images and the set of additional images are merged using the computing device to create a second set of training images. A second classifier is trained using a second process running on the computing device using the second set of training images. A set of unclassified images are classified using the second classifier thereby creating a set of classified images. The first classifier and the second classifier employ different classification methods.
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公开(公告)号：US20100158356A1
公开(公告)日：2010-06-24
申请号：US12341587
申请日：2008-12-22
IPC分类号： G06K9/62
CPC分类号： G06K9/6256
摘要： A system and method for improved classification. A first classifier is trained using a first process running on at least one computing device using a first set of training images relating to a class of images. A set of additional images are selected using the first classifier from a source of additional images accessible to the computing device. The first set of training images and the set of additional images are merged using the computing device to create a second set of training images. A second classifier is trained using a second process running on the computing device using the second set of training images. A set of unclassified images are classified using the second classifier thereby creating a set of classified images. The first classifier and the second classifier employ different classification methods.
摘要翻译： 一种改进分类的系统和方法。 使用使用与一类图像相关的第一组训练图像在至少一个计算装置上运行的第一进程训练第一分类器。 使用来自计算设备可访问的附加图像的源的第一分类器来选择一组附加图像。 使用计算设备将第一组训练图像和一组附加图像合并以创建第二组训练图像。 使用第二组训练图像在计算设备上运行的第二进程训练第二分类器。 使用第二分类器对一组未分类图像进行分类，从而创建一组分类图像。 第一分类器和第二分类器采用不同的分类方法。
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5.发明申请Automatically Ranking Multimedia Objects Identified in Response to Search Queries 审中-公开自动排序响应搜索查询识别的多媒体对象公开(公告)号：US20100299303A1
公开(公告)日：2010-11-25
申请号：US12470437
申请日：2009-05-21
CPC分类号： G06F16/3346 , G06F16/435
摘要： Construct a statistical model for a plurality of multimedia objects identified in response to a search query, the statistical model comprising a plurality of probabilities, wherein each of the multimedia objects uniquely corresponding to a different one of a plurality of sets of feature values, each of the feature values of each of the sets of feature values being a characterization of the multimedia object corresponding to the set of feature values, and each of the probabilities being calculated for a different one of the multimedia objects based on the set of feature values corresponding to the multimedia object. Rank the multimedia objects based on their corresponding probabilities, such that a multimedia object having a relatively higher probability is ranked relatively higher.
摘要翻译： 构建响应于搜索查询识别的多个多媒体对象的统计模型，所述统计模型包括多个概率，其中每个所述多媒体对象唯一地对应于多组特征值中的不同的一组特征值， 每个特征值集合的特征值是与特征值集合相对应的多媒体对象的表征，并且基于与多个对象的特征值对应的集合来为不同的多媒体对象计算每个概率 多媒体对象。 基于其对应的概率对多媒体对象进行排序，使得具有较高概率的多媒体对象的排名相对较高。
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公开(公告)号：US20090327168A1
公开(公告)日：2009-12-31
申请号：US12147342
申请日：2008-06-26
申请人： Kilian Quirin Weinberger , Anirban Dasgupta , Raghu Ramakrishnan , David Reiley , Martin Andre Monroe Zinkevich , Bo Pang , Daniel Kifer
发明人： Kilian Quirin Weinberger , Anirban Dasgupta , Raghu Ramakrishnan , David Reiley , Martin Andre Monroe Zinkevich , Bo Pang , Daniel Kifer
IPC分类号： G06F3/048
CPC分类号： H04L51/12
摘要： Embodiments are directed towards employing a playful incentive to encourage users to provide feedback that is useable to train a classifier. The classifier being associated with any of a variety of different settings, including but not limited to classifying: messages as ham/spam, images, advertising, bookmarking, music, videos, photographs, shopping, or the like. An animated image, such as a pet, provides an interface to the classifier that encourages and responds to user feedback. Users may share their classifiers or aspects thereof with other users to enable a community of knowledge to be applied to a classification task, while preserving privacy of the user feedback. One form of sharing may be within the context of a competitive game. Various evaluations may be performed on a classifier to indicate user feedback consistency, or quality. Classifiers may also be used to provide users with advertisements, products, or services based on the user's feedback.
摘要翻译： 实施例旨在采用有趣的激励来鼓励用户提供可用于训练分类器的反馈。 分类器与各种不同的设置相关联，包括但不限于分类：消息作为火腿/垃圾邮件，图像，广告，书签，音乐，视频，照片，购物等。 动画图像（如宠物）为分类器提供了一个界面，鼓励和响应用户反馈。 用户可以与其他用户共享他们的分类器或其方面，以使知识社区能够应用于分类任务，同时保持用户反馈的隐私。 一种共享的形式可能在竞争性游戏的背景下。 可以在分类器上执行各种评估，以指示用户反馈一致性或质量。 分类器也可以用于根据用户的反馈向用户提供广告，产品或服务。
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公开(公告)号：US20090287618A1
公开(公告)日：2009-11-19
申请号：US12123270
申请日：2008-05-19
CPC分类号： H04L51/12 , G06N99/005
摘要： Embodiments are directed towards using a community of weighted results from local and global message classifiers to determine whether a message is spam. Each local classifier may receive a message that is to be evaluated to determine whether it is spam. A local classifier receives the message and performs a classification of the message. The local classifier may receive predictions of whether the message is spam from at least one global classifier. The local and global predictions are combined using, in one embodiment, a regression analysis to generate a single local message classification. Combining the local and global predictions is directed towards enabling a community of predictions to be used to classify messages. The user may then re-classify this output, which in turn is used as feedback to modify weights to the local and received global predictions for a next message.
摘要翻译： 实施例旨在使用来自本地和全局消息分类器的加权结果的社区来确定消息是否是垃圾邮件。 每个本地分类器可能会收到要评估的消息，以确定它是否是垃圾邮件。 本地分类器接收消息并对消息进行分类。 本地分类器可以接收来自至少一个全局分类器的消息是否为垃圾邮件的预测。 在一个实施例中，使用回归分析来生成单个本地消息分类来组合本地和全局预测。 结合本地和全球预测，旨在使一个预测社区能够用于对消息进行分类。 然后，用户可以对该输出进行重新分类，该输出又被用作反馈以对下一个消息的本地和接收的全局预测修改权重。
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公开(公告)号：US08433993B2
公开(公告)日：2013-04-30
申请号：US12491217
申请日：2009-06-24
IPC分类号： G06F17/00
CPC分类号： G06F17/30053
摘要： Methods and system for rendering context aware multimedia content include identifying a plurality of multimedia content that is uploaded for rendering. The uploaded multimedia content is examined to determine metadata associated with each of the plurality of multimedia contents. Contextual information associated with the metadata is identified and a grouping of the multimedia content into a plurality of groups is performed based on the contextual information. Each of the plurality of groups is then integrated into one or more photo stories. The photo stories are defined and rendered as content rich documents.
摘要翻译： 用于呈现上下文感知多媒体内容的方法和系统包括识别上传以呈现的多个多媒体内容。 检查上传的多媒体内容以确定与多个多媒体内容中的每一个相关联的元数据。 识别与元数据相关联的上下文信息，并且基于上下文信息来执行多媒体内容到多个组中的分组。 然后将多个组中的每个组合成一个或多个照片故事。 照片故事被定义和呈现为内容丰富的文档。
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公开(公告)号：US20110029561A1
公开(公告)日：2011-02-03
申请号：US12533475
申请日：2009-07-31
IPC分类号： G06F17/30
CPC分类号： G06F17/30247 , G06F17/30265 , G06F17/30271
摘要： A search engine determines a set of other images that are similar to a user-selected image, and presents those other images to the user. In determining whether two images are sufficiently similar to each other to merit presentation of one, the search engine determines a Euclidean distance between separate feature vectors that are associated with each of the images. Each such vector indicates diverse types of information that is known about the associated image. The types of information included within such a vector may include attributes that reflect visual characteristics that are visible in an image, verbal tags that have been associated with the image users in a community of users, concepts derived from those tags, coordinates that reflect a geographic location at which a camera that produced the image was when the camera produced the image, and concepts related to groups with which the image is associated.
摘要翻译： 搜索引擎确定与用户选择的图像类似的一组其他图像，并将这些其他图像呈现给用户。 在确定两个图像是否彼此足够相似以表现出一个图像时，搜索引擎确定与每个图像相关联的独立特征向量之间的欧氏距离。 每个这样的向量表示关于相关图像已知的不同类型的信息。 包括在这样的向量内的信息的类型可以包括反映在图像中可见的视觉特征的属性，已经与用户社区中的图像用户相关联的语言标签，从那些标签导出的概念，反映地理的坐标 相机产生图像时产生图像的相机的位置以及与图像相关联的组相关的概念。
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公开(公告)号：US09710759B2
公开(公告)日：2017-07-18
申请号：US12686240
申请日：2010-01-12
CPC分类号： G06N99/005 , G06Q10/107
摘要： In accordance with one aspect, methods and apparatus facilitate the filtering of unsolicited bulk electronic mail (email) sent from spammers. A plurality of recipient patterns for a plurality of emails from known spammers is logged. A plurality of recipient patterns for a plurality of emails from known non-spammers is also logged. A probabilistic model for predicting whether an unknown sender identity is a spammer is generated or modified based on the logged recipient patterns for the emails from known spammers and known non-spammers.
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