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1. 发明授权

US11640494B1 Systems and methods for construction, maintenance, and improvement of knowledge representations 有权
公开(公告)号：US11640494B1
公开(公告)日：2023-05-02
申请号：US17135218
申请日：2020-12-28
申请人： Digital Reasoning Systems, Inc.
发明人： Timothy Wayne Estes , James Johnson Gardner , Matthew Russell , Phillip Daniel Michalak
IPC分类号： G06F40/169 , G06Q10/107 , G06F40/30 , G06F40/40 , G06F40/211
摘要： In one aspect, the present disclosure relates to a method which, in one example embodiment, can include receiving text data that includes at least unstructured data and wherein the text data is associated with a plurality of messages communicated between a plurality of entities. The method can also include determining relationships between the entities, based on the text data associated with the plurality of messages, and generating, from a knowledge base assembled from at least the text data, a response to a user interaction representing a query for information that corresponds to at least one of the entities and indicates information on one or more of the determined relationships between the entities. The method can also include detecting a deviation in communication between the entities that indicates unauthorized disclosure of information between a first entity and a second entity.

2. 发明授权

US08457950B1 System and method for coreference resolution 有权
标题翻译：共同解析的系统和方法
公开(公告)号：US08457950B1
公开(公告)日：2013-06-04
申请号：US13666722
申请日：2012-11-01
申请人： Digital Reasoning Systems, Inc.
发明人： James Johnson Gardner , Vishnuvardhan Balluru , Phillip Daniel Michalak , Kenneth Loran Graham , John Wagster
IPC分类号： G10L15/00
CPC分类号： G10L15/1815
摘要： According to one aspect, a method for coreference resolution is provided. In one embodiment, the method includes receiving a segment of text that includes mentions corresponding to entities. A first feature vector is generated based on one or more features associated with a first mention, and a second feature vector is generated based on based on one or more features associated with a second mention. A measure of similarity between the first feature vector and second feature vector is computed and, based on the computed measure of similarity, it is determined if the first mention and the second mention both correspond to the same entity.
摘要翻译：根据一个方面，提供了一种用于融合解析的方法。在一个实施例中，该方法包括接收包括对应于实体的提及的文本段。基于与第一提及相关联的一个或多个特征生成第一特征向量，并且基于与第二提及相关联的一个或多个特征来生成第二特征向量。计算第一特征向量和第二特征向量之间的相似性度量，并且基于所计算的相似度测量，确定第一提及和第二提及是否对应于相同实体。

3. 发明授权

US09697192B1 Systems and methods for construction, maintenance, and improvement of knowledge representations 有权
公开(公告)号：US09697192B1
公开(公告)日：2017-07-04
申请号：US15154951
申请日：2016-05-14
申请人： Digital Reasoning Systems, Inc.
发明人： Timothy Wayne Estes , James Johnson Gardner , Matthew Russell , Phillip Daniel Michalak
IPC分类号： G06F17/28 , G06F17/24 , G06F17/27
CPC分类号： G06F17/241 , G06F17/271 , G06F17/2785 , G06F17/28 , G06Q10/107
摘要： In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages and creating semantic annotations to the text data to generate annotated messages. Creating the semantic annotations can include generating, at least in part by at least one trained statistical language model, predictive labels as annotations corresponding to language patterns associated with the text data. The method further includes aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store, and performing, based on information from the message store and associated with the messages, global analytics functions. The global analytics functions can include identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, to form an updated semantic annotation, and back-propagating the updated semantic annotation into training data for further language model training.

4. 发明授权

US09348815B1 Systems and methods for construction, maintenance, and improvement of knowledge representations 有权
标题翻译：构建，维护和改进知识表示的系统和方法
公开(公告)号：US09348815B1
公开(公告)日：2016-05-24
申请号：US14705899
申请日：2015-05-06
申请人： Digital Reasoning Systems, Inc.
发明人： Timothy Wayne Estes , James Johnson Gardner , Matthew Russell , Phillip Daniel Michalak
IPC分类号： G06F15/18 , G06F17/27 , G06F17/30 , G06F17/28
CPC分类号： G06F17/241 , G06F17/271 , G06F17/2785 , G06F17/28 , G06Q10/107
摘要： In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages, creating semantic annotations to the text data to generate one or more annotated messages, and aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store. The method can further include performing, based on information from the message store and associated with the one or more messages, one or more global analytics functions that include: identifying an annotation error in the semantic annotations created using the trained statistical language model, updating the respective semantic annotation to correct the annotation error, and back-propagating corrected data corresponding to the updated semantic annotation into training data for further language model training.
摘要翻译：在一个方面，本公开涉及一种在一个示例性实施例中的方法，其可以包括读取对应于消息的文本数据，为文本数据创建语义注释以生成一个或多个注释消息，以及聚集注释消息并存储信息与消息存储中的聚合注释消息相关联。该方法还可以包括：基于来自消息存储器的信息并与一个或多个消息相关联地执行一个或多个全局分析功能，其包括：识别使用训练的统计语言模型创建的语义注释中的注释错误，相应的语义注释来校正注释错误，并将对应于更新的语义注释的校正数据反向传播到用于进一步的语言模型训练的训练数据中。

5. 发明授权

US09058317B1 System and method for machine learning management 有权
标题翻译：机器学习管理系统与方法
公开(公告)号：US09058317B1
公开(公告)日：2015-06-16
申请号：US14444326
申请日：2014-07-28
申请人： Digital Reasoning Systems, Inc.
发明人： James Johnson Gardner , Terrence Scot Clausing , Phillip Daniel Michalak , Jared William Bunting , Keith Ellis Massey
IPC分类号： G06F17/00 , G06F17/24 , G06N99/00
CPC分类号： G06N99/005 , G06F17/2755
摘要： According to one aspect, a method for machine learning management is provided. In one embodiment, the method includes receiving a first segment of text data, identifying data features corresponding to a sequence of characters in the first segment of text data, and generating predictive annotations to the sequence of characters based at least in part on the identified data features. The method can also include identifying inaccurate annotations generated according to the predictive annotations, correcting the identified inaccurate annotations, generating one or more sets of model training data incorporating the corrected annotations, and monitoring progress of annotations made to a second segment of text data associated with the first segment of text data by a plurality of collaborating users of a plurality of managed computers.
摘要翻译：根据一方面，提供了一种用于机器学习管理的方法。在一个实施例中，该方法包括接收文本数据的第一段，识别对应于文本数据的第一段中的字符序列的数据特征，以及至少部分地基于所识别的数据来生成字符序列的预测注释特征。该方法还可以包括识别根据预测注释生成的不准确注释，校正所识别的不准确注释，生成并入校正注释的一组或多组模型训练数据，以及监视与第二段文本数据相关联的注释的进度由多个被管理计算机的多个协作用户的第一段文本数据。

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