专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US08788498B2 Labeling data samples using objective questions 有权
标题翻译：使用客观问题标注数据样本
公开(公告)号：US08788498B2
公开(公告)日：2014-07-22
申请号：US12484255
申请日：2009-06-15
申请人： Anitha Kannan , Krishnaram Kenthapadi , John C. Shafer , Ariel Fuxman
发明人： Anitha Kannan , Krishnaram Kenthapadi , John C. Shafer , Ariel Fuxman
IPC分类号： G06F17/30
CPC分类号： G06Q10/10
摘要： Described is a technology for obtaining labeled sample data. Labeling guidelines are converted into binary yes/no questions regarding data samples. The questions and data samples are provided to judges who then answer the questions for each sample. The answers are input to a label assignment algorithm that associates a label with each sample based upon the answers. If the guidelines are modified and previous answers to the binary questions are maintained, at least some of the previous answers may be used in re-labeling the samples in view of the modification.
摘要翻译：描述了用于获得标记的样本数据的技术。标签指南被转换为关于数据样本的二进制是/否问题。问题和数据样本提供给那些随后回答每个样本的问题的法官。将答案输入到标签分配算法，该算法根据答案将标签与每个样本相关联。如果修改了指南并维护了二进制问题的以前的答案，则鉴于修改，至少可以使用一些以前的答案来重新标记样本。

2. 发明申请

US20100318539A1 LABELING DATA SAMPLES USING OBJECTIVE QUESTIONS 有权
标题翻译：使用目标问题标记数据样本
公开(公告)号：US20100318539A1
公开(公告)日：2010-12-16
申请号：US12484255
申请日：2009-06-15
申请人： Anitha Kannan , Krishnaram Kenthapadi , John C. Shafer , Ariel Fuxman
发明人： Anitha Kannan , Krishnaram Kenthapadi , John C. Shafer , Ariel Fuxman
IPC分类号： G06F17/30
CPC分类号： G06Q10/10
摘要： Described is a technology for obtaining labeled sample data. Labeling guidelines are converted into binary yes/no questions regarding data samples. The questions and data samples are provided to judges who then answer the questions for each sample. The answers are input to a label assignment algorithm that associates a label with each sample based upon the answers. If the guidelines are modified and previous answers to the binary questions are maintained, at least some of the previous answers may be used in re-labeling the samples in view of the modification.
摘要翻译：描述了用于获得标记的样本数据的技术。标签指南被转换为关于数据样本的二进制是/否问题。问题和数据样本提供给那些随后回答每个样本的问题的法官。将答案输入到标签分配算法，该算法根据答案将标签与每个样本相关联。如果修改了指南并维护了二进制问题的以前的答案，则鉴于修改，至少可以使用一些以前的答案来重新标记样本。

3. 发明授权

US08838432B2 Image annotations on web pages 有权
标题翻译：网页上的图片注释
公开(公告)号：US08838432B2
公开(公告)日：2014-09-16
申请号：US13366385
申请日：2012-02-06
申请人： Simon John Baker , Juliet Anne Bernstein , Krishnan Ramnath , Anitha Kannan , Dahua Lin , Qifa Ke , Matthew Uyttendaele
发明人： Simon John Baker , Juliet Anne Bernstein , Krishnan Ramnath , Anitha Kannan , Dahua Lin , Qifa Ke , Matthew Uyttendaele
IPC分类号： G06F17/20 , G06F17/27 , G06F17/21
CPC分类号： G06F17/241 , G06F17/30247 , G06F17/30861
摘要： An image in a web page may be annotated after deriving information about an image when the image may be displayed on multiple web pages. The web pages that show the image may be analyzed in light of each other to determine metadata about the image, then various additional content may be added to the image. The additional content may be hyperlinks to other webpages. The additional content may be displayed as annotations on top of the images and in other manners. Many embodiments may perform searching, analysis, and classification of images prior to the web page being served.
摘要翻译：当图像可以在多个网页上显示时，可以在导出关于图像的信息之后注释网页中的图像。可以相互分析示出图像的网页以确定关于图像的元数据，然后可以向图像添加各种附加内容。附加内容可能是其他网页的超链接。附加内容可以在图像之上以其他方式显示为注释。许多实施例可以在提供网页之前执行图像的搜索，分析和分类。

4. 发明申请

US20120314941A1 ACCURATE TEXT CLASSIFICATION THROUGH SELECTIVE USE OF IMAGE DATA 有权
标题翻译：通过选择性使用图像数据的精确文本分类
公开(公告)号：US20120314941A1
公开(公告)日：2012-12-13
申请号：US13158484
申请日：2011-06-13
申请人： Anitha Kannan , Partha Pratim Talukdar , Nikhil Rasiwasia , Qifa Ke , Rakesh Agrawal
发明人： Anitha Kannan , Partha Pratim Talukdar , Nikhil Rasiwasia , Qifa Ke , Rakesh Agrawal
IPC分类号： G06K9/62
CPC分类号： G06K9/6268 , G06K9/6227 , G06K9/6293
摘要： Product images are used in conjunction with textual descriptions to improve classifications of product offerings. By combining cues from both text and image descriptions associated with products, implementations enhance both the precision and recall of product description classifications within the context of web-based commerce search. Several implementations are directed to improving those areas where text-only approaches are most unreliable. For example, several implementations use image signals to complement text classifiers and improve overall product classification in situations where brief textual product descriptions use vocabulary that overlaps with multiple diverse categories. Other implementations are directed to using text and images “training sets” to improve automated classifiers including text-only classifiers. Certain implementations are also directed to learning a number of three-way image classifiers focused only on “confusing categories” of the text signals to improve upon those specific areas where text-only classification is weakest.
摘要翻译：产品图像与文本描述结合使用，以改进产品分类。通过结合来自与产品相关的文本和图像描述的提示，实现在基于网络的商业搜索的上下文中增强了产品描述分类的精度和回收。几个实现旨在改进那些仅文本方法最不可靠的领域。例如，在简短的文本产品描述使用与多个不同类别重叠的词汇的情况下，多个实现使用图像信号来补充文本分类器并改进整体产品分类。其他实现涉及使用文本和图像训练集来改进自动分类器，包括纯文本分类器。某些实现也针对学习一些三维图像分类器，仅针对混淆文本信号的类别，以改进文本分类最弱的特定区域。

5. 发明申请

US20110289026A1 Matching Offers to Known Products 有权
标题翻译：与已知产品匹配优惠
公开(公告)号：US20110289026A1
公开(公告)日：2011-11-24
申请号：US12783753
申请日：2010-05-20
申请人： Anitha Kannan , Inmar-Ella Givoni
发明人： Anitha Kannan , Inmar-Ella Givoni
IPC分类号： G06F17/30 , G06F15/18
CPC分类号： G06F17/30997 , G06Q30/00
摘要： A method and apparatus for electronically matching an electronic offer to structured data for a product offering is disclosed. The structure data is reviewed and a dictionary of terms for each attribute from the structure data is created. Attributes in unstructured text may be determined. Each pair of the attributes (name and value) from the unstructured data and the structured data are obtained, the attribute pairs of the structured data and the unstructured data and compared and a similarity level is calculated for the matching the attribute pairs. The structured data pair that has the highest similarity score to the unstructured data pair is selected and returned.
摘要翻译：公开了一种用于将电子报价电子匹配用于产品产品的结构化数据的方法和装置。审查结构数据，并从结构数据中创建每个属性的术语词典。可以确定非结构化文本中的属性。获得来自非结构化数据和结构化数据的每对属性（名称和值），结构化数据的属性对和非结构化数据，并进行比较，并计算相似度水平以匹配属性对。选择并返回与非结构化数据对具有最高相似性得分的结构化数据对。

6. 发明授权

US07729531B2 Identifying repeated-structure elements in images 有权
标题翻译：识别图像中的重复结构元素
公开(公告)号：US07729531B2
公开(公告)日：2010-06-01
申请号：US11533297
申请日：2006-09-19
申请人： John Winn , Anitha Kannan , Carsten Rother
发明人： John Winn , Anitha Kannan , Carsten Rother
IPC分类号： G06K9/62
CPC分类号： G06K9/4638
摘要： Many problems in the fields of image processing and computer vision relate to creating good representations of information in images of objects in scenes. We provide a system for learning repeated-structure elements from one or more input images. The repeated-structure elements are patches that may be single pixels or coherent groups of pixels of varying shape, size and appearance (where those shapes and sizes are not pre-specified). Input images are mapped to a single output image using offset maps to specify the mapping. A joint probability distribution on the offset maps, output image and input images is specified and an unsupervised learning process is used to learn the offset maps and output image. The learnt output image comprises repeated-structure elements. This shape and appearance information captured in the learnt repeated-structure elements may be used for object recognition and many other tasks.
摘要翻译：图像处理和计算机视觉领域的许多问题涉及在场景中的对象的图像中创建信息的良好表示。我们提供一个用于从一个或多个输入图像学习重复结构元素的系统。重复结构元素是可以是单个像素或具有不同形状，大小和外观（其中这些形状和尺寸未被预先指定）的像素的相干组的补丁。使用偏移映射将输入图像映射到单个输出图像以指定映射。指定偏移图，输出图像和输入图像上的联合概率分布，并使用无监督的学习过程来学习偏移图和输出图像。所学习的输出图像包括重复结构元素。在学习的重复结构元素中捕获的这种形状和外观信息可以用于对象识别和许多其他任务。

7. 发明申请

US20130204608A1 IMAGE ANNOTATIONS ON WEB PAGES 有权
标题翻译：网页上的图像注释
公开(公告)号：US20130204608A1
公开(公告)日：2013-08-08
申请号：US13366385
申请日：2012-02-06
申请人： Simon John BAKER , Juliet Anne BERNSTEIN , Krishnan RAMNATH , Anitha KANNAN , Dahua LIN , Qifa KE , Matthew UYTTENDAELE
发明人： Simon John BAKER , Juliet Anne BERNSTEIN , Krishnan RAMNATH , Anitha KANNAN , Dahua LIN , Qifa KE , Matthew UYTTENDAELE
IPC分类号： G06F17/27 , G06F17/00
CPC分类号： G06F17/241 , G06F17/30247 , G06F17/30861
摘要： An image in a web page may be annotated after deriving information about an image when the image may be displayed on multiple web pages. The web pages that show the image may be analyzed in light of each other to determine metadata about the image, then various additional content may be added to the image. The additional content may be hyperlinks to other webpages. The additional content may be displayed as annotations on top of the images and in other manners. Many embodiments may perform searching, analysis, and classification of images prior to the web page being served.
摘要翻译：当图像可以在多个网页上显示时，可以在导出关于图像的信息之后注释网页中的图像。可以相互分析示出图像的网页以确定关于图像的元数据，然后可以向图像添加各种附加内容。附加内容可能是其他网页的超链接。附加内容可以在图像之上以其他方式显示为注释。许多实施例可以在提供网页之前执行图像的搜索，分析和分类。

8. 发明申请

US20130144854A1 MODELING ACTIONS FOR ENTITY-CENTRIC SEARCH 有权
标题翻译：建立实体中央搜索行动
公开(公告)号：US20130144854A1
公开(公告)日：2013-06-06
申请号：US13311581
申请日：2011-12-06
申请人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
发明人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
IPC分类号： G06F17/30
CPC分类号： G06F17/30867
摘要： In one embodiment, a web service engine server 104 may predict a successive action by a user based on an entity reference 302. The web service engine server 104 may identify an entity reference 302 in a data transmission caused by a user. The web service engine server 104 may determine from the data transmission a user intention towards the entity reference 302 using an intention model based on a transmission log. The web service engine server 104 may predict a related successive web action option 522 for the entity reference 302 based on the user intention.
摘要翻译：在一个实施例中，网络服务引擎服务器104可以基于实体参考302来预测用户的连续动作。网络服务引擎服务器104可以在由用户引起的数据传输中识别实体参考302。 Web服务引擎服务器104可以使用基于传输日志的意图模型从数据传输确定用户对实体参考302的意图。 Web服务引擎服务器104可以基于用户意图预测实体参考302的相关的连续web动作选项522。

9. 发明授权

US08417651B2 Matching offers to known products 有权
标题翻译：与已知产品匹配
公开(公告)号：US08417651B2
公开(公告)日：2013-04-09
申请号：US12783753
申请日：2010-05-20
申请人： Anitha Kannan , Inmar-Ella Givoni
发明人： Anitha Kannan , Inmar-Ella Givoni
IPC分类号： G06F15/18
CPC分类号： G06F17/30997 , G06Q30/00
摘要： A method and apparatus for electronically matching an electronic offer to structured data for a product offering is disclosed. The structure data is reviewed and a dictionary of terms for each attribute from the structure data is created. Attributes in unstructured text may be determined. Each pair of the attributes (name and value) from the unstructured data and the structured data are obtained, the attribute pairs of the structured data and the unstructured data and compared and a similarity level is calculated for the matching the attribute pairs. The structured data pair that has the highest similarity score to the unstructured data pair is selected and returned.
摘要翻译：公开了一种用于将电子报价电子匹配用于产品产品的结构化数据的方法和装置。审查结构数据，并从结构数据中创建每个属性的术语词典。可以确定非结构化文本中的属性。获得来自非结构化数据和结构化数据的每对属性（名称和值），结构化数据的属性对和非结构化数据，并进行比较，并计算相似度水平以匹配属性对。选择并返回与非结构化数据对具有最高相似性得分的结构化数据对。

10. 发明申请

US20110066650A1 QUERY CLASSIFICATION USING IMPLICIT LABELS 有权
标题翻译：使用隐含标签的查询分类
公开(公告)号：US20110066650A1
公开(公告)日：2011-03-17
申请号：US12560427
申请日：2009-09-16
申请人： Ariel D. Fuxman , Anitha Kannan , Andrew Brian Goldberg , Rakesh Agrawal
发明人： Ariel D. Fuxman , Anitha Kannan , Andrew Brian Goldberg , Rakesh Agrawal
IPC分类号： G06F17/30
CPC分类号： G06F17/30693
摘要： Described is a technology for automatically generating labeled training data for training a classifier based upon implicit information associated with the data. For example, whether a query has commercial intent can be classified based upon whether the query was submitted at a commercial website's search portal, as logged in a toolbar log. Positive candidate query-related data is extracted from the toolbar log based upon the associated implicit information. A click log is processed to obtain negative query-related data. The labeled training data is automatically generated by separating at least some of the positive candidate query data from the remaining positive candidate query data based upon the negative query data. The labeled training data may be used to train a classifier, such as to classify an online search query as having a certain type of intent or not.
摘要翻译：描述了一种用于根据与数据相关联的隐含信息自动生成用于训练分类器的标记训练数据的技术。例如，查询是否具有商业意图可以根据在商业网站的搜索门户网站上提交的查询进行分类，如登录在工具栏日志中。基于相关联的隐含信息，从工具栏日志中提取正候选查询相关数据。处理点击日志以获取负查询相关数据。基于负查询数据，将剩余的正候选查询数据中的至少一些正候选查询数据分离出来，自动生成标示训练数据。标记的训练数据可以用于训练分类器，例如将在线搜索查询分类为具有某种类型的意图。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式