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    • 3. 发明申请
    • Automatic Task Extraction and Calendar Entry
    • 自动任务提取和日历条目
    • US20130007648A1
    • 2013-01-03
    • US13170660
    • 2011-06-28
    • Michael GamonSaliha AzzamYizheng CaiNicholas CaldwellYe-Yi Wang
    • Michael GamonSaliha AzzamYizheng CaiNicholas CaldwellYe-Yi Wang
    • G06F3/048
    • 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.
    • 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。
    • 9. 发明申请
    • Technique for document editorial quality assessment
    • 文件编辑质量评估技术
    • US20060100852A1
    • 2006-05-11
    • US10969119
    • 2004-10-20
    • Michael GamonAnthony Aue
    • Michael GamonAnthony Aue
    • G06F17/27
    • G06F17/271G06F17/2785
    • 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.
    • 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。
    • 10. 发明授权
    • Functionality for normalizing linguistic items
    • 语言项目规范化的功能
    • US08909516B2
    • 2014-12-09
    • US13313034
    • 2011-12-07
    • Julie A. MederoDaniel S. MorrisLucretia H. VanderwendeMichael Gamon
    • Julie A. MederoDaniel S. MorrisLucretia H. VanderwendeMichael Gamon
    • G06F17/20G06F17/28G06F17/27G06F17/21G10L21/00G10L15/26G10L17/00
    • G06F17/27
    • 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.
    • 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。