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公开(公告)号:US08630972B2
公开(公告)日:2014-01-14
申请号:US12143765
申请日:2008-06-21
申请人: Michael Gamon , Sumit Basu , Dmitriy A. Belenko , Danyel A Fisher , Arnd C. Konig , Matthew F. Hurst
发明人: Michael Gamon , Sumit Basu , Dmitriy A. Belenko , Danyel A Fisher , Arnd C. Konig , Matthew F. Hurst
CPC分类号: G06F17/30014
摘要: An overwhelming number of articles are available everyday via the internet. Unfortunately, it is impossible to peruse more than a handful, and it is difficult to ascertain an article's social context. The techniques disclosed herein address this problem by harnessing implicit and explicit contextual information from social media. By extracting text surrounding a hyperlink to an article in a post and assessing the article as a function of content surrounding the hyperlink, an article's social context is determined and presented. Additionally, articles that are sufficiently similar in content may be grouped to establish a many-to-one relationship between posts and an article, creating a more accurate assessment.
摘要翻译: 每天通过互联网可以获得绝大多数的文章。 不幸的是,不可能仔细阅读,而且很难确定文章的社会背景。 本文所揭示的技术通过利用来自社交媒体的隐含和明确的上下文信息来解决这个问题。 通过提取文章中超文本文章中的文章,并根据超链接的内容评估文章,确定并呈现文章的社会语境。 此外,内容足够相似的文章可以被分组以在帖子和文章之间建立多对一关系,从而创建更准确的评估。
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公开(公告)号:US20090319449A1
公开(公告)日:2009-12-24
申请号:US12143765
申请日:2008-06-21
申请人: Michael Gamon , Sumit Basu , Dmitriy A. Belenko , Danyel A. Fisher , Arnd C. Konig , Matthew F. Hurst
发明人: Michael Gamon , Sumit Basu , Dmitriy A. Belenko , Danyel A. Fisher , Arnd C. Konig , Matthew F. Hurst
CPC分类号: G06F17/30014
摘要: An overwhelming number of articles are available everyday via the internet. Unfortunately, it is impossible to peruse more than a handful, and it is difficult to ascertain an article's social context. The techniques disclosed herein address this problem by harnessing implicit and explicit contextual information from social media. By extracting text surrounding a hyperlink to an article in a post and assessing the article as a function of content surrounding the hyperlink, an article's social context is determined and presented. Additionally, articles that are sufficiently similar in content may be grouped to establish a many-to-one relationship between posts and an article, creating a more accurate assessment.
摘要翻译: 每天通过互联网可以获得绝大多数的文章。 不幸的是,不可能仔细阅读,而且很难确定文章的社会背景。 本文所揭示的技术通过利用来自社交媒体的隐含和明确的上下文信息来解决这个问题。 通过提取文章中超文本文章中的文章,并根据超链接的内容评估文章,确定并呈现文章的社会语境。 此外,内容足够相似的文章可以被分组以在帖子和文章之间建立多对一关系,从而创建更准确的评估。
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公开(公告)号:US20130159219A1
公开(公告)日:2013-06-20
申请号:US13325386
申请日:2011-12-14
申请人: Patrick Pantel , Michael Gamon , Yoav Y. Artzi
发明人: Patrick Pantel , Michael Gamon , Yoav Y. Artzi
CPC分类号: G06N20/00
摘要: Different advantageous embodiments provide for response prediction. A social element is received by a prediction mechanism. A feature set is generated for the social element. A prediction is generated using the feature set and a prediction model.
摘要翻译: 不同的有利实施例提供了响应预测。 一个社会因素被预测机制所接受。 为社交元素生成一个特征集。 使用特征集和预测模型生成预测。
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公开(公告)号:US20110179061A1
公开(公告)日:2011-07-21
申请号:US12818718
申请日:2010-06-18
申请人: Venkat Pradeep Chilakamarri , Nicholas Caldwell , Saliha Azzam , Yizheng Cai , Benjamin Edward Childs , Arun Chitrapu , Steven Dimmick , Michael Gamon , Bernhard SJ Kohlmeier , Shiun-Zu Kuo , Jonathan C. Ludwig , Kimberly Manis , Courtney Anne O'Keefe , Diego Perez Del Carpio , Tu Huy Phan , Kevin Powell , Jignesh Shah , Ashish Sharma , Paulus Willem ter Horst , Mukta Pramod Walvekar , Ye-Yi Wang
发明人: Venkat Pradeep Chilakamarri , Nicholas Caldwell , Saliha Azzam , Yizheng Cai , Benjamin Edward Childs , Arun Chitrapu , Steven Dimmick , Michael Gamon , Bernhard SJ Kohlmeier , Shiun-Zu Kuo , Jonathan C. Ludwig , Kimberly Manis , Courtney Anne O'Keefe , Diego Perez Del Carpio , Tu Huy Phan , Kevin Powell , Jignesh Shah , Ashish Sharma , Paulus Willem ter Horst , Mukta Pramod Walvekar , Ye-Yi Wang
IPC分类号: G06F17/30
CPC分类号: G06Q10/00
摘要: An analysis module, when triggered by a synchronization framework when a new data item is added to a project data store, runs a series of analysis feature extractors on the new content. An analysis may be conducted, and features of interest may be extracted from the data item. The analysis utilizes natural language processing, as well as other technologies, to provide an automatic or semi-automatic extraction of information. The extracted features of interest are saved as metadata within the project data store, and are associated with the data item from which it was extracted. The analysis module may be utilized to discover additional information that may be gleaned from content that is already in the project data store.
摘要翻译: 分析模块在将新数据项添加到项目数据存储时由同步框架触发时,在新内容上运行一系列分析功能提取器。 可以进行分析,并且可以从数据项中提取感兴趣的特征。 该分析利用自然语言处理以及其他技术来提供信息的自动或半自动提取。 提取的兴趣特征作为元数据保存在项目数据存储中,并与提取的数据项相关联。 可以使用分析模块来发现可能已经在项目数据存储中的内容收集的附加信息。
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公开(公告)号:US07788086B2
公开(公告)日:2010-08-31
申请号:US11105619
申请日:2005-04-14
CPC分类号: G06F17/30707 , G06F17/274
摘要: The present invention provides a system for identifying, extracting, clustering and analyzing sentiment-bearing text. In one embodiment, the invention implements a pipeline capable of accessing raw text and presenting it in a highly usable and intuitive way.
摘要翻译: 本发明提供一种用于识别,提取,聚类和分析情感文本的系统。 在一个实施例中,本发明实现了能够访问原始文本并且以高度可用和直观的方式呈现它的流水线。
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公开(公告)号:US20060100852A1
公开(公告)日:2006-05-11
申请号:US10969119
申请日:2004-10-20
申请人: Michael Gamon , Anthony Aue
发明人: Michael Gamon , Anthony Aue
IPC分类号: G06F17/27
CPC分类号: G06F17/271 , G06F17/2785
摘要: A computer-implemented system and method for assessing the editorial quality of a textual unit (document, paragraph or sentence) is provided. The method includes generating a plurality of training-time feature vectors by automatically extracting features from first and last versions of training documents. The method also includes training a machine-learned classifier based on the plurality of training-time feature vectors. A run-time feature vector is generated for the textual unit to be assessed by automatically extracting features from the textual unit. The run-time feature vector is evaluated using the machine-learned classifier to provide an assessment of the editorial quality of the textual unit.
摘要翻译: 提供了一种用于评估文本单元(文档,段落或句子)的编辑质量的计算机实现的系统和方法。 该方法包括通过自动提取来自训练文档的第一和最后版本的特征来生成多个训练时特征向量。 该方法还包括基于多个训练时间特征向量训练机器学习分类器。 通过自动从文本单元中提取特征,为要评估的文本单元生成运行时特征向量。 运行时特征向量使用机器学习分类器进行评估,以提供对文本单元的编辑质量的评估。
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公开(公告)号:US08909516B2
公开(公告)日:2014-12-09
申请号:US13313034
申请日:2011-12-07
CPC分类号: G06F17/27
摘要: Computing functionality converts an input linguistic item into a normalized linguistic item, representing a normalized counterpart of the input linguistic item. In one environment, the input linguistic item corresponds to a complaint by a person receiving medical care, and the normalized linguistic item corresponds to a definitive and error-free version of that complaint. In operation, the computing functionality uses plural reference resources to expand the input linguistic item, creating an expanded linguistic item. The computing functionality then forms a graph based on candidate tokens that appear in the expanded linguistic item, and then finds a shortest path through the graph; that path corresponds to the normalized linguistic item. The computing functionality may use a statistical language model to assign weights to edges in the graph, and to determine whether the normalized linguistic incorporates two or more component linguistic items.
摘要翻译: 计算功能将输入语言项目转换为归一化语言项目,表示输入语言项目的归一化对应项。 在一个环境中,输入语言项目对应于接受医疗护理的人的投诉,而归一化语言项目对应于该投诉的确定和无错误的版本。 在操作中,计算功能使用多个参考资源来扩展输入语言项,创建扩展的语言项。 然后,计算功能基于出现在扩展语言项目中的候选令牌形成图形,然后找到通过图形的最短路径; 该路径对应于归一化语言项。 计算功能可以使用统计语言模型来向图中的边缘分配权重,并且确定归一化语言是否包含两个或多个组件语言项。
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公开(公告)号:US20130007648A1
公开(公告)日:2013-01-03
申请号:US13170660
申请日:2011-06-28
申请人: Michael Gamon , Saliha Azzam , Yizheng Cai , Nicholas Caldwell , Ye-Yi Wang
发明人: Michael Gamon , Saliha Azzam , Yizheng Cai , Nicholas Caldwell , Ye-Yi Wang
IPC分类号: G06F3/048
摘要: Automatically detected and identified tasks and calendar items from electronic communications may be populated into one or more tasks applications and calendaring applications. Text content retrieved from one or more electronic communications may be extracted and parsed for determining whether keywords or terms contained in the parsed text may lead to a classification of the text content or part of the text content as a task. Identified tasks may be automatically populated into a tasks application. Similarly, text content from such sources may be parsed for keywords and terms that may be identified as indicating calendar items, for example, meeting requests. Identified calendar items may be automatically populated into a calendar application as a calendar entry.
摘要翻译: 来自电子通信的自动检测和识别的任务和日历项可以被填充到一个或多个任务应用程序和日历应用程序中。 可以提取并解析从一个或多个电子通信检索的文本内容,以便确定包含在解析文本中的关键字或术语是否可以导致将文本内容或部分文本内容分类为任务。 已识别的任务可以自动填充到任务应用程序中。 类似地,可以针对可以被识别为指示日历项目的关键字和术语(例如会议请求)来解析来自这些源的文本内容。 识别的日历项可以自动地作为日历条目填充到日历应用中。
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公开(公告)号:US20110179049A1
公开(公告)日:2011-07-21
申请号:US12818667
申请日:2010-06-18
申请人: Nicholas Caldwell , Venkat Pradeep Chilakamarri , Saliha Azzam , Yizheng Cai , Michael Calcagno , Benjamin Edward Childs , Arun Chitrapu , Steven Dimmick , Michael Gamon , Bernhard SJ Kohlmeier , Shiun-Zu Kuo , Jonathan C. Ludwig , Kimberly Manis , Courtney Anne O'Keefe , Diego Perez Del Carpio , Tu Huy Phan , Kevin Powell , Jignesh Shah , Ashish Sharma , Paulus Willem ter Horst , Mukta Pramod Walvekar , Ye-Yi Wang
发明人: Nicholas Caldwell , Venkat Pradeep Chilakamarri , Saliha Azzam , Yizheng Cai , Michael Calcagno , Benjamin Edward Childs , Arun Chitrapu , Steven Dimmick , Michael Gamon , Bernhard SJ Kohlmeier , Shiun-Zu Kuo , Jonathan C. Ludwig , Kimberly Manis , Courtney Anne O'Keefe , Diego Perez Del Carpio , Tu Huy Phan , Kevin Powell , Jignesh Shah , Ashish Sharma , Paulus Willem ter Horst , Mukta Pramod Walvekar , Ye-Yi Wang
IPC分类号: G06F17/30
CPC分类号: G06Q10/00
摘要: Project-related data may be aggregated from various data sources, given context, and may be stored in a data repository or organizational knowledge base that may be available to and accessed by others. Documents, emails, contact information, calendar data, social networking data, and any other content that is related to a project may be brought together within a single user interface, irrespective of its data type. A user may organize and understand content, discover relevant information, and act on it without regard to where the information resides or how it was created.
摘要翻译: 项目相关数据可以从各种数据源(给定上下文)聚合,并且可以存储在数据存储库或组织知识库中,该数据存储库或组织知识库可被其他人可用和访问。 文档,电子邮件,联系信息,日历数据,社交网络数据以及与项目相关的任何其他内容可以在单个用户界面内汇集在一起,而不管其数据类型如何。 用户可以组织和理解内容,发现相关信息并对其进行操作,而不考虑信息所在的位置或其创建方式。
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公开(公告)号:US20060200341A1
公开(公告)日:2006-09-07
申请号:US11105619
申请日:2005-04-14
申请人: Simon Corston-Oliver , Anthony Aue , Eric Ringger , Michael Gamon
发明人: Simon Corston-Oliver , Anthony Aue , Eric Ringger , Michael Gamon
IPC分类号: G06F17/28
CPC分类号: G06F17/30707 , G06F17/274
摘要: The present invention provides a system for identifying, extracting, clustering and analyzing sentiment-bearing text. In one embodiment, the invention implements a pipeline capable of accessing raw text and presenting it in a highly usable and intuitive way.
摘要翻译: 本发明提供一种用于识别,提取,聚类和分析情感文本的系统。 在一个实施例中,本发明实现了能够访问原始文本并且以高度可用和直观的方式呈现它的流水线。
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