公开(公告)号：US20160162456A1

公开(公告)日：2016-06-09

申请号：US14964517

申请日：2015-12-09

申请人： Robert J. Munro ,  Schuyler D. Erle ,  Christopher Walker ,  Sarah K. Luger ,  Jason Brenier ,  Gary C. King ,  Paul A. Tepper ,  Ross Mechanic ,  Andrew Gilchrist-Scott ,  Jessica D. Long ,  James B. Robinson ,  Brendan D. Callahan ,  Michelle Casbon ,  Ujjwal Sarin ,  Aneesh Nair ,  Veena Basavaraj ,  Tripti Saxena ,  Edgar Nunez ,  Martha G. Hinrichs ,  Haley Most ,  Tyler J. Schnoebelen

发明人： Robert J. Munro ,  Schuyler D. Erle ,  Christopher Walker ,  Sarah K. Luger ,  Jason Brenier ,  Gary C. King ,  Paul A. Tepper ,  Ross Mechanic ,  Andrew Gilchrist-Scott ,  Jessica D. Long ,  James B. Robinson ,  Brendan D. Callahan ,  Michelle Casbon ,  Ujjwal Sarin ,  Aneesh Nair ,  Veena Basavaraj ,  Tripti Saxena ,  Edgar Nunez ,  Martha G. Hinrichs ,  Haley Most ,  Tyler J. Schnoebelen

IPC分类号： G06F17/24 ,  G06F17/22 ,  G06F17/28

CPC分类号： G06F17/30598 ,  G06F3/0482 ,  G06F17/2241 ,  G06F17/241 ,  G06F17/272 ,  G06F17/2785 ,  G06F17/28 ,  G06F17/2809 ,  G06F17/30011 ,  G06F17/30401 ,  G06F17/30445 ,  G06F17/30604 ,  G06F17/30654 ,  G06F17/30705 ,  G06F17/30734 ,  G06F17/30864 ,  G06Q50/01

摘要： Methods are presented for generating a natural language model. The method may comprise: ingesting training data representative of documents to be analyzed by the natural language model, generating a hierarchical data structure comprising at least two topical nodes within which the training data is to be subdivided into by the natural language model, selecting a plurality of documents among the training data to be annotated, generating an annotation prompt for each document configured to elicit an annotation about said document indicating which node among the at least two topical nodes said document is to be classified into, receiving the annotation based on the annotation prompt; and generating the natural language model using an adaptive machine learning process configured to determine patterns among the annotations for how the documents in the training data are to be subdivided according to the at least two topical nodes of the hierarchical data structure.

摘要翻译： 提出了生成自然语言模型的方法。 该方法可以包括：摄取表示要由自然语言模型分析的文档的训练数据，生成包括至少两个主题节点的分层数据结构，训练数据将在该节点内被自然语言模型细分，选择多个 在要注释的训练数据中生成文档的注释提示，为每个文档生成关于所述文档的注释的注释提示，该注释指示所述文档中的至少两个主题节点中的哪个节点被分类，基于注释接收注释 提示; 以及使用自适应机器学习过程来生成所述自然语言模型，所述自适应机器学习过程被配置为根据所述分级数据结构的所述至少两个主题节点来确定所述注释中的模式如何根据所述训练数据中的文档被细分。

公开(公告)号：US20160162458A1

公开(公告)日：2016-06-09

申请号：US14964522

申请日：2015-12-09

申请人： Robert J. Munro ,  Christopher Walker ,  Sarah K. Luger ,  Jason Brenier ,  Paul A. Tepper ,  Ross Mechanic ,  Andrew Gilchrist-Scott ,  Gary C. King ,  Brendan D. Callahan ,  Tyler J. Schnoebelen ,  Edgar Nunez ,  Haley Most

发明人： Robert J. Munro ,  Christopher Walker ,  Sarah K. Luger ,  Jason Brenier ,  Paul A. Tepper ,  Ross Mechanic ,  Andrew Gilchrist-Scott ,  Gary C. King ,  Brendan D. Callahan ,  Tyler J. Schnoebelen ,  Edgar Nunez ,  Haley Most

IPC分类号： G06F17/24 ,  G06F3/0482

CPC分类号： G06F17/241 ,  G06F3/0482 ,  G06F16/243 ,  G06F16/24532 ,  G06F16/285 ,  G06F16/288 ,  G06F16/3329 ,  G06F16/35 ,  G06F16/367 ,  G06F16/93 ,  G06F16/951 ,  G06F17/2241 ,  G06F17/272 ,  G06F17/2785 ,  G06F17/28 ,  G06F17/2809 ,  G06Q50/01

摘要： Methods and systems are disclosed for creating and linking a series of interfaces configured to display information and receive confirmation of classifications made by a natural language modeling engine to improve organization of a collection of documents into an hierarchical structure. In some embodiments, the interfaces may display to an annotator a plurality of labels of potential classifications for a document as identified by a natural language modeling engine, collect annotated responses from the annotator, aggregate the annotated responses across other annotators, analyze the accuracy of the natural language modeling engine based on the aggregated annotated responses, and predict accuracies of the natural language modeling engine's classifications of the documents.

摘要翻译： 公开了用于创建和链接被配置为显示信息并且接收由自然语言建模引擎进行的分类的确认的一系列接口以改进文档集合到分层结构中的组合的方法和系统。 在一些实施例中，接口可以向注释器显示由自然语言建模引擎识别的文档的潜在分类的多个标签，从注释器收集注释的响应，在其他注释器之间聚合注释的响应，分析 基于聚合注释响应的自然语言建模引擎，并预测自然语言建模引擎对文档分类的准确性。

公开(公告)号：US20160162476A1

公开(公告)日：2016-06-09

申请号：US14964511

申请日：2015-12-09

申请人： Robert J. Munro ,  Schuyler D. Erle ,  Tyler J. Schnoebelen ,  Jason Brenier ,  Jessica D. Long ,  Brendan D. Callahan ,  Paul A. Tepper ,  Edgar Nunez

发明人： Robert J. Munro ,  Schuyler D. Erle ,  Tyler J. Schnoebelen ,  Jason Brenier ,  Jessica D. Long ,  Brendan D. Callahan ,  Paul A. Tepper ,  Edgar Nunez

IPC分类号： G06F17/28

CPC分类号： G06F17/30598 ,  G06F3/0482 ,  G06F17/2241 ,  G06F17/241 ,  G06F17/272 ,  G06F17/2785 ,  G06F17/28 ,  G06F17/2809 ,  G06F17/30011 ,  G06F17/30401 ,  G06F17/30445 ,  G06F17/30604 ,  G06F17/30654 ,  G06F17/30705 ,  G06F17/30734 ,  G06F17/30864 ,  G06Q50/01

摘要： Systems and methods are presented for the automatic placement of rules applied to topics in a logical hierarchy when conducting natural language processing. In some embodiments, a method includes: accessing, at a child node in a logical hierarchy, at least one rule associated with the child node; identifying a percolation criterion associated with a parent node to the child node, said percolation criterion indicating that the at least one rule associated with the child node is to be associated also with the parent node; associating the at least one rule with the parent node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the parent node; accessing the document for natural language processing; and determining whether the document is to be classified into the parent node or the child node based on the at least one rule.

摘要翻译： 提出了系统和方法，用于在进行自然语言处理时自动放置适用于逻辑层次结构中主题的规则。 在一些实施例中，一种方法包括：在逻辑层级中的子节点处访问与所述子节点相关联的至少一个规则; 识别与所述子节点的父节点相关联的渗透标准，所述渗透标准指示与所述子节点相关联的所述至少一个规则也将与所述父节点相关联; 将所述至少一个规则与所述父节点相关联，使得所述至少一个规则定义用于确定所述文档是否也被分类为所述父节点的第二因素; 访问文档进行自然语言处理; 以及基于所述至少一个规则来确定所述文档是否被分类到所述父节点或所述子节点。

公开(公告)号：US09495345B2

公开(公告)日：2016-11-15

申请号：US14964511

申请日：2015-12-09

申请人： Robert J. Munro ,  Schuyler D. Erle ,  Tyler J. Schnoebelen ,  Jason Brenier ,  Jessica D. Long ,  Brendan D. Callahan ,  Paul A. Tepper ,  Edgar Nunez

发明人： Robert J. Munro ,  Schuyler D. Erle ,  Tyler J. Schnoebelen ,  Jason Brenier ,  Jessica D. Long ,  Brendan D. Callahan ,  Paul A. Tepper ,  Edgar Nunez

IPC分类号： G06F17/27 ,  G06F17/21 ,  G06F17/24 ,  G06F17/28 ,  G06F17/22 ,  G06F3/0482 ,  G06F17/30

CPC分类号： G06F17/30598 ,  G06F3/0482 ,  G06F17/2241 ,  G06F17/241 ,  G06F17/272 ,  G06F17/2785 ,  G06F17/28 ,  G06F17/2809 ,  G06F17/30011 ,  G06F17/30401 ,  G06F17/30445 ,  G06F17/30604 ,  G06F17/30654 ,  G06F17/30705 ,  G06F17/30734 ,  G06F17/30864 ,  G06Q50/01

摘要： Systems and methods are presented for the automatic placement of rules applied to topics in a logical hierarchy when conducting natural language processing. In some embodiments, a method includes: accessing, at a child node in a logical hierarchy, at least one rule associated with the child node; identifying a percolation criterion associated with a parent node to the child node, said percolation criterion indicating that the at least one rule associated with the child node is to be associated also with the parent node; associating the at least one rule with the parent node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the parent node; accessing the document for natural language processing; and determining whether the document is to be classified into the parent node or the child node based on the at least one rule.

摘要翻译： 提出了系统和方法，用于在进行自然语言处理时自动放置适用于逻辑层次结构中主题的规则。 在一些实施例中，一种方法包括：在逻辑层级中的子节点处访问与所述子节点相关联的至少一个规则; 识别与所述子节点的父节点相关联的渗透标准，所述渗透标准指示与所述子节点相关联的所述至少一个规则也将与所述父节点相关联; 将所述至少一个规则与所述父节点相关联，使得所述至少一个规则定义用于确定所述文档是否也被分类为所述父节点的第二因素; 访问文档进行自然语言处理; 以及基于所述至少一个规则来确定所述文档是否被分类到所述父节点或所述子节点。