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1. 发明申请

US20100257440A1 HIGH PRECISION WEB EXTRACTION USING SITE KNOWLEDGE 审中-公开
标题翻译：使用站点知识的高精度网络提取
公开(公告)号：US20100257440A1
公开(公告)日：2010-10-07
申请号：US12416381
申请日：2009-04-01
申请人： Meghana Kshirsagar , Rajeev Rastogi , Sandeepkumar Bhuramal Satpal , Srinivasan H. Sengamedu , Venu Satuluri
发明人： Meghana Kshirsagar , Rajeev Rastogi , Sandeepkumar Bhuramal Satpal , Srinivasan H. Sengamedu , Venu Satuluri
IPC分类号： G06F17/21 , G06F17/00
CPC分类号： G06F16/986
摘要： Techniques for high precision web extraction using site knowledge are provided. Portions of repeating text are identified in unlabeled web pages from a particular web site. Based on the portions of repeating text, the unlabeled web pages are partitioned into a set of segments. Multiple labels are assigned to respectively corresponding multiple attributes in the set of segments, where assigning the multiple labels comprises applying a classification model to each separate segment in the set of segments. First one or more labels are identified that were erroneously assigned to one or more attributes in the set of segments. Second one or more correct labels for the one or more attributes are determined. The first one or more labels in the set of segments are corrected by assigning the second one or more labels to the one or more attributes.
摘要翻译：提供使用现场知识的高精度网络提取技术。在特定网站的未标记的网页中标识重复文本的部分。基于重复文本的部分，未标记的网页被分割成一组段。多个标签被分配给该组段中的相应的多个属性，其中分配多个标签包括将分类模型应用于该组段中的每个单独的段。识别出错误地分配给该组段中的一个或多个属性的第一个或多个标签。确定一个或多个属性的第二个一个或多个正确标签。通过将第二个一个或多个标签分配给一个或多个属性来校正该组段中的第一个或多个标签。

2. 发明申请

US20100223214A1 AUTOMATIC EXTRACTION USING MACHINE LEARNING BASED ROBUST STRUCTURAL EXTRACTORS 审中-公开
标题翻译：使用机器学习的结构提升机自动提取
公开(公告)号：US20100223214A1
公开(公告)日：2010-09-02
申请号：US12395586
申请日：2009-02-27
申请人： Alok S. Kirpal , Sandeepkumar Bhuramal Satpal , Meghana Kshirsagar , Srinivasan H. Sengamedu
发明人： Alok S. Kirpal , Sandeepkumar Bhuramal Satpal , Meghana Kshirsagar , Srinivasan H. Sengamedu
IPC分类号： G06F15/18
CPC分类号： G06F16/86
摘要： A method and apparatus for automatically extracting information from a large number of documents through applying machine learning techniques and exploiting structural similarities among documents. A machine learning model is trained to have at least 50% accuracy. The trained machine learning model is used to identify information attributes in a sample of pages from a cluster of structurally similar documents. A structure-specific model of the cluster is created by compiling a list of top-K locations for each attribute identified by the trained machine learning model in the sample. These top-K lists are used to extract information from the pages of the cluster from which the sample of pages was taken.
摘要翻译：一种通过应用机器学习技术和利用文档之间的结构相似性自动从大量文档中提取信息的方法和装置。训练机器学习模型至少有50％的准确性。训练有素的机器学习模型用于识别来自结构类似文档的集群的页面样本中的信息属性。通过编译样本中经过训练的机器学习模型识别的每个属性的顶部K位置的列表来创建集群的结构特定模型。这些顶级K列表用于从从中获取页面样本的群集页面中提取信息。

3. 发明申请

US20110167063A1 TECHNIQUES FOR CATEGORIZING WEB PAGES 有权
标题翻译：分类网页的技术
公开(公告)号：US20110167063A1
公开(公告)日：2011-07-07
申请号：US12652624
申请日：2010-01-05
申请人： Ashwin Tengli , Rajeev Rastogi , Jeyashankher Ramamirtham , Srinivasan H. Sengamedu , Sandeepkumar Bhuramal Satpal
发明人： Ashwin Tengli , Rajeev Rastogi , Jeyashankher Ramamirtham , Srinivasan H. Sengamedu , Sandeepkumar Bhuramal Satpal
IPC分类号： G06F17/30
CPC分类号： G06F7/00 , G06F17/30834 , G06F17/30864
摘要： Web pages are efficiently categorized in a data processor without analyzing the content of the web pages. According to at least one embodiment, data is maintained that represents sample URLs grouped into a plurality of clusters. The sample URLs of a cluster are used to produce a URL regular expression pattern (“URL-regex”) that differentiates the sample URLs of the cluster from the sample URLs of other clusters and that covers at least a specified percentage of the sample URLs in the cluster. The process of producing a URL-regex is repeated for each of the clusters producing a URL-regex for each cluster. Web pages are then categorized into one of the clusters by determining which of the URL-regex patterns produced for the clusters match URLs that refer to the web pages. Thus, a web page may be categorized based on a URL that refers to the web page without having to obtain and analyze the content of the web page.
摘要翻译：在不分析网页内容的情况下，网页被有效地分类到数据处理器中。根据至少一个实施例，维护表示分组为多个集群的抽样URL的数据。集群的示例URL用于生成URL正则表达式模式（“URL-regex”），用于将集群的示例URL与其他集群的示例URL进行区分，并且至少包含指定百分比的示例URL 集群。为每个集群重复生成URL-regex的过程，为每个集群生成一个URL-regex。然后，通过确定针对集群产生的哪个URL-regex模式与引用网页的URL匹配，将网页分类到其中一个集群。因此，可以基于引用网页的URL来分类网页，而不必获取和分析网页的内容。

4. 发明授权

US09087507B2 Aural skimming and scrolling 有权
标题翻译：听觉滑动和滚动
公开(公告)号：US09087507B2
公开(公告)日：2015-07-21
申请号：US11600346
申请日：2006-11-15
申请人： Srinivasan H. Sengamedu
发明人： Srinivasan H. Sengamedu
IPC分类号： G10L13/00 , G10L13/08 , G10L21/00 , G10L25/00 , G06F17/00 , G06F17/20 , G10L13/027
CPC分类号： G10L13/00 , G10L13/027 , G10L13/08
摘要： Computer-based skimming and scrolling of aurally presented information is described. Different levels of skimming are achieved in aural presentations with allowing a user to navigate an aural presentation according to significant points identified within an information source. The significant points are identified using various indicia that suggest logical arrangements for the information contained within the source, such as semantics, syntax, typography, formatting, named entities, and markup tags. The identified significant points signal changes in playback mode for the audio presentation, such as different tones, pitches, volumes, or voices. Similar indicia may be used to generate identifying markers from the information source that can be aurally presented in lieu of the information source itself to allow for aural scrolling of the information.
摘要翻译：描述了基于计算机的撇取和滚动显示的信息。在听觉呈现中实现不同程度的撇号，允许用户根据信息源中识别的重要点导航听觉呈现。使用针对源中包含的信息（例如语义，语法，排版，格式化，命名实体和标记标签）提供逻辑排列的各种标记来识别重要点。识别的有效点信号在音频呈现的回放模式中变化，例如不同的音调，音调，音量或语音。类似的标记可以用于从信息源产生识别标记，其可以被听觉地呈现以代替信息源本身以允许信息的听觉滚动。

5. 发明授权

US08498978B2 Slideshow video file detection 有权
标题翻译：幻灯片视频文件检测
公开(公告)号：US08498978B2
公开(公告)日：2013-07-30
申请号：US12345674
申请日：2008-12-30
申请人： Venkatesh Babu Radhakrishnan , Srinivasan H. Sengamedu
发明人： Venkatesh Babu Radhakrishnan , Srinivasan H. Sengamedu
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30781
摘要： Slideshow video file detection. A method includes receiving a search query for video files of a desired type. A portion of a video file is extracted. A frame difference based histogram and an active pixel based histogram are generated for the portion. Further, the frame difference based histogram and an active pixel based histogram are provided to a machine learning tool. An indicator is determined for the portion based on a plurality of parameters. The video file is classified as the desired type based on the indicator. The video file is provided to the user.
摘要翻译：幻灯片视频文件检测。一种方法包括接收对期望类型的视频文件的搜索查询。提取视频文件的一部分。为该部分生成基于帧差分的直方图和基于活动像素的直方图。此外，基于帧差的直方图和基于活动像素的直方图被提供给机器学习工具。基于多个参数确定该部分的指示符。视频文件根据指示符分类为所需类型。该视频文件被提供给用户。

6. 发明授权

US07962468B2 System and method for providing image labeling game using CBIR 有权
标题翻译：使用CBIR提供图像标注游戏的系统和方法
公开(公告)号：US07962468B2
公开(公告)日：2011-06-14
申请号：US12104954
申请日：2008-04-17
申请人： Subhajit Sanyal , Srinivasan H. Sengamedu , Sriram J. Sathish
发明人： Subhajit Sanyal , Srinivasan H. Sengamedu , Sriram J. Sathish
IPC分类号： G06F7/00
CPC分类号： G06F17/30247
摘要： The present invention is directed towards systems and methods for improving image labeling using content-based image retrieval. The method according to one embodiment of the present invention comprises selecting an image query and identifying a first image related to the image query. The method then selects a plurality of second images related to the first image and assigns weights to the plurality of second images. Finally, the method displays the first images and the second images on a client device.
摘要翻译：本发明涉及使用基于内容的图像检索来改进图像标注的系统和方法。根据本发明的一个实施例的方法包括选择图像查询并识别与图像查询相关的第一图像。然后，该方法选择与第一图像相关的多个第二图像，并为多个第二图像分配权重。最后，该方法在客户端设备上显示第一个图像和第二个图像。

7. 发明申请

US20100228738A1 ADAPTIVE DOCUMENT SAMPLING FOR INFORMATION EXTRACTION 审中-公开
标题翻译：采集信息提取的自适应文件
公开(公告)号：US20100228738A1
公开(公告)日：2010-09-09
申请号：US12398162
申请日：2009-03-04
申请人： Rupesh R. Mehta , Srinivasan H. Sengamedu
发明人： Rupesh R. Mehta , Srinivasan H. Sengamedu
IPC分类号： G06F17/30 , G06F17/21
CPC分类号： G06F17/241 , G06F16/951 , G06F16/9558
摘要： A method and apparatus for improved sampling documents for training sets input to information extraction systems is provided, which improves the recall and robustness of wrapper extraction. A passive sampling technique provides a list of documents to present for human annotation ordered by representativeness of the document based on structural and content statistics. Thus, the document with the most interesting attributes and which is most representative of the cluster of structurally similar documents to which the document pertains is presented for annotation first. The problem is mapped to classical ‘Set-Cover’ problem and solved using greedy approach. An active sampling technique refines and reorders the sample list produced by the passive sampling technique after initial annotations, based on the human annotation, spatial boundaries of the documents, and structural and content statistics. The proposed techniques work at a site level and perform page-level structural analysis using XPath-term frequency, XPath-document frequency, and XPath-importance.
摘要翻译：提供了一种用于改进对信息提取系统输入的训练集的抽样文档的方法和装置，其提高了包装提取的召回和鲁棒性。被动采样技术提供了基于结构和内容统计的文档代表性排序的人体注释的文档列表。因此，首先提出了具有最有趣属性，最具代表性的结构相似的文档集合的文档。问题被映射到古典的“封面”问题，并使用贪心的方法来解决。基于人的注释，文档的空间边界以及结构和内容统计，主动采样技术在初始注释之后，对被动采样技术产生的样本列表进行优化和重新排序。所提出的技术在现场级别工作，并使用XPath项目频率，XPath文档频率和XPath重要性进行页面级结构分析。

8. 发明申请

US20090157576A1 MEASURING AND LIMITING DISTRACTIONS ON COMPUTER DISPLAYS 审中-公开
标题翻译：计算机显示器的测量和限制分配
公开(公告)号：US20090157576A1
公开(公告)日：2009-06-18
申请号：US11958183
申请日：2007-12-17
申请人： Malcolm Slaney , Srinivasan H. Sengamedu
发明人： Malcolm Slaney , Srinivasan H. Sengamedu
IPC分类号： G06E1/00
CPC分类号： G06F16/9577
摘要： Techniques are described herein for determining a distractibility measure for an item to be displayed on a display. The distractibility measure for an item is determined based on the individual distractibility measures for one or more of: the static distraction of the item, the onset response of the item, the optic-flow motion of the item, and the change in velocity of objects in the item. Each individual distractibility measure can be further multiplied by a weighting factor which affects the composition of the distractibility measure for the item. The distractibility measure for the item can be further based on the size of the item, how far away the item is from a primary content on the display, and the distractibility measure of the primary content on the display. The distractibility measure for the item can be compared to a maximum level of distractibility for automatically determining whether the item should be displayed on the display. Finally, the techniques described herein can be combined with other techniques which detect specific types of visual content in an item.
摘要翻译：这里描述了用于确定要在显示器上显示的物品的分散性测量的技术。项目的分散性测量是基于以下一个或多个的单独的分散性测量来确定的：项目的静态分心，项目的开始响应，项目的光流运动以及物体的速度变化在项目中。每个单独的分散性测量可以进一步乘以影响该项目的分散性测量的组成的加权因子。项目的分散性测量可以进一步基于项目的大小，项目与显示器上的主要内容有多远，以及显示器上主要内容的分散性测量。可以将项目的分散性度量与最大程度的分散性进行比较，以自动确定项目是否应显示在显示屏上。最后，本文描述的技术可以与检测项目中的特定类型的视觉内容的其他技术组合。

9. 发明授权

US08731284B2 Method and system for detecting image spam 有权
标题翻译：检测图像垃圾邮件的方法和系统
公开(公告)号：US08731284B2
公开(公告)日：2014-05-20
申请号：US12339740
申请日：2008-12-19
申请人： Sriram J. Sathish , Srinivasan H. Sengamedu
发明人： Sriram J. Sathish , Srinivasan H. Sengamedu
IPC分类号： G06K9/00
CPC分类号： G06K9/40 , G06K9/342 , G06K2209/01
摘要： Methods and systems are provided that may be used to determine a whether an image contains spam. In one particular embodiment, an image is transformed and spam is detected based on such a transformed image.
摘要翻译：提供了可用于确定图像是否包含垃圾邮件的方法和系统。在一个特定实施例中，基于这样的变换图像来变换图像并且检测垃圾邮件。

10. 发明授权

US08108257B2 Delayed advertisement insertion in videos 有权
标题翻译：视频延迟广告插入
公开(公告)号：US08108257B2
公开(公告)日：2012-01-31
申请号：US11877008
申请日：2007-10-23
申请人： Srinivasan H. Sengamedu
发明人： Srinivasan H. Sengamedu
IPC分类号： G06Q40/00
CPC分类号： G06F17/30882 , G06F17/30014 , G06F17/30855 , G06Q10/0637 , G06Q30/02 , G06Q30/0276 , G06Q30/0277
摘要： A method for achieving uninterrupted interactivity for user watching a video yet clicking on an advertisement is provided. A method for delayed interactivity is provided herein. Delayed interactivity is implemented in the form of delayed insertions. When a user clicks on an object in hypervideo, presentation of or any action on the related information is deferred rather than played immediately. Delayed interactivity also is implemented in the form of video bookmarks. When a user clicks on an actual advertisement, related information is stored, i.e., bookmarked, along with video content. In this way, the user can pursue the related information at a later time and at the user's convenience.
摘要翻译：提供了一种用于实现用户观看视频而点击广告的不间断交互的方法。本文提供了延迟交互性的方法。延迟互动以延迟插入的形式实现。当用户点击超视频中的对象时，相关信息的呈现或任何操作被推迟，而不是立即播放。延迟交互也以视频书签的形式实现。当用户点击实际的广告时，与视频内容一起存储相关信息，即书签。以这种方式，用户可以在稍后的时间和用户方便地追踪相关信息。

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