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    Systems and methods that determine intent of data and respond to the data based on the intent
    3.
    发明授权
    Systems and methods that determine intent of data and respond to the data based on the intent 有权
    确定数据意图并根据意图响应数据的系统和方法

    公开(公告)号：US07496500B2

    公开(公告)日：2009-02-24

    申请号：US10867626

    申请日：2004-06-15

    申请人： David R. Reed ,  Eric K. Ringger ,  Michael Gamon ,  Richard G. Campbell ,  Robert G. Atkinson ,  Simon H. Corston ,  Malcolm E. Pearson

    发明人： David R. Reed ,  Eric K. Ringger ,  Michael Gamon ,  Richard G. Campbell ,  Robert G. Atkinson ,  Simon H. Corston ,  Malcolm E. Pearson

    IPC分类号： G06F17/27 ,  G06F15/16 ,  G06F15/173

    CPC分类号： G06Q10/107

    摘要： The present invention relates to systems and methods that determine intent for received data (e.g., email, voice, graphics . . . ) and respond to the data based on the intent. The systems and methods employ various combinations of features based on shallow and deep linguistic analysis (e.g., semantic and syntactic) to yield very high accuracy. The systems and methods analyze and categorize received data to locate data that can include intent. This data can be further refined by extracting features related to the intent. The features can be utilized by a classifier to determine the intent. If the intent warrants a response, the data are further scrutinized and reformulated to generate a description that is indicative of the intent. The reformulation can include representing the features in a logical form, transforming the form and generating a description of the intent that can be presented to a user visually and/or audibly.

    摘要翻译： 本发明涉及确定接收到的数据（例如，电子邮件，语音，图形...）的意图并基于意图响应数据的系统和方法。 系统和方法采用基于浅层和深层语言分析（例如语义和句法）的特征的各种组合，以产生非常高的精度。 系统和方法分析和分类接收到的数据以定位可包括意图的数据。 可以通过提取与意图相关的特征来进一步改进该数据。 分类器可以利用这些特征来确定意图。 如果意图保证有回应，则会对数据进行仔细检查和重新设计，以生成表示意图的描述。 重新制定可以包括以逻辑形式表示特征，转换形式并生成可以以视觉和/或听觉呈现给用户的意图的描述。

    Technique for document editorial quality assessment
    4.
    发明申请
    Technique for document editorial quality assessment 有权
    文件编辑质量评估技术

    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。

    Technique for document editorial quality assessment
    6.
    发明授权
    Technique for document editorial quality assessment 有权
    文件编辑质量评估技术

    公开(公告)号：US07835902B2

    公开(公告)日：2010-11-16

    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： G06F17/28 ,  G06F17/21 ,  G06F7/00

    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。

    Functionality for normalizing linguistic items
    10.
    发明授权
    Functionality for normalizing linguistic items 有权
    语言项目规范化的功能

    公开(公告)号：US08909516B2

    公开(公告)日：2014-12-09

    申请号：US13313034

    申请日：2011-12-07

    申请人： Julie A. Medero ,  Daniel S. Morris ,  Lucretia H. Vanderwende ,  Michael Gamon

    发明人： Julie A. Medero ,  Daniel S. Morris ,  Lucretia H. Vanderwende ,  Michael Gamon

    IPC分类号： G06F17/20 ,  G06F17/28 ,  G06F17/27 ,  G06F17/21 ,  G10L21/00 ,  G10L15/26 ,  G10L17/00

    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。