公开(公告)号：US20120233132A1

公开(公告)日：2012-09-13

申请号：US13044873

申请日：2011-03-10

Applicant: Dnyanesh Rajpathak

Inventor： Dnyanesh Rajpathak

IPC: G06F17/30

CPC classification number: G06F17/30734 ,  G06F17/2795

Abstract: A method and system for splitting a text document into individual sentences using sentence boundary detection, and establishing co-relationships between terms which are present in the same sentence. A document corpus, or collection of text records, is provided, containing text with terms to be extracted. The text records in the document corpus are divided into individual sentences, using a set of rules for sentence boundary detection. The individual sentences are then analyzed to extract and correlate terms, such as parts and symptoms, symptoms and actions, or parts and failure modes. The correlated terms are then validated based on frequency of occurrence, with term pairs being considered valid if their frequency of occurrence exceeds a minimum frequency threshold. The validated term correlations can be used for fault model development, document classification, and document clustering.

Abstract translation: 一种使用句子边界检测将文本文档分割成单个句子的方法和系统，并且在同一句子中存在的术语之间建立共同关系。 提供文档语料库或文本记录集合，其中包含要提取的术语的文本。 文档语料库中的文本记录被分为单独的句子，使用一组用于句子边界检测的规则。 然后分析单个句子以提取和关联术语，如部分和症状，症状和动作，或部分和失败模式。 然后根据出现频率对相关项进行验证，如果出现的频率超过最小频率阈值，则术语对被认为是有效的。 验证的术语相关性可用于故障模型开发，文档分类和文档聚类。

公开(公告)号：US20120232905A1

公开(公告)日：2012-09-13

申请号：US13328726

申请日：2011-12-16

Applicant: Dnyanesh Rajpathak ,  Soumen De

Inventor： Dnyanesh Rajpathak ,  Soumen De

IPC: G10L15/18

CPC classification number: G06F17/2785

Abstract: A method and system for developing reliability models from unstructured text documents, such as text verbatim descriptions from service technicians. An ontology, or data model, and heuristic rules are used to identify and extract failure modes and parts from the text verbatim comments associated with specific labor codes from service events. Like-meaning but differently-worded terms are then merged using text similarity scoring techniques. The resultant failure modes are used to create enhanced reliability models, where component reliability is predicted in terms of individual failure modes instead of aggregated for the component. The enhanced reliability models provide improved reliability prediction for the component, and also provides insight into aspects of the component design which can be improved in the future.

Abstract translation: 从非结构化文本文档开发可靠性模型的方法和系统，如维修技术人员的文字逐字描述。 本体或数据模型和启发式规则用于从服务事件中与特定劳动力代码相关联的文本逐字记录中识别和提取故障模式和部分。 然后使用文本相似性评分技术合并相似意义但是不同的措辞术语。 所得到的故障模式用于创建增强的可靠性模型，其中可以根据单个故障模式来预测组件的可靠性，而不是组件的聚合。 增强的可靠性模型为组件提供了改进的可靠性预测，并且还提供了对将来可以改进的组件设计的方面的洞察。

公开(公告)号：US20120233112A1

公开(公告)日：2012-09-13

申请号：US13045310

申请日：2011-03-10

Applicant: Dnyanesh Rajpathak ,  Satnam Singh

Inventor： Dnyanesh Rajpathak ,  Satnam Singh

IPC: G06N5/02

CPC classification number: G06F17/2785

Abstract: A method and system for developing fault models from unstructured text documents, such as text verbatim descriptions from customers and service technicians. An ontology, or data model, and heuristic rules are used to identify and extract descriptive terms from the text verbatim document. The descriptive terms are then classified into types, including symptoms, failure modes, and parts. Like-meaning but differently-worded descriptive terms are then merged using text similarity scoring techniques. The resultant symptoms, failure modes, parts, and correlations are then assembled into a fault model, which can be used for real-time fault diagnosis onboard a vehicle, or off-board at service shops.

Abstract translation: 从非结构化文本文档开发故障模型的方法和系统，如客户和维修技术人员的文字逐字描述。 本体论或数据模型和启发式规则用于从文本逐字文本中识别和提取描述性术语。 然后将描述性术语分为类型，包括症状，失败模式和部分。 然后使用文本相似性评分技术合并相似意义但不同的措辞描述性术语。 然后将所产生的症状，故障模式，部件和相关性组合成故障模型​​，其可以用于车辆上的实时故障诊断或者在服务商店的车外故障诊断。

公开(公告)号：US08666982B2

公开(公告)日：2014-03-04

申请号：US13267173

申请日：2011-10-06

Applicant: Dnyanesh Rajpathak ,  Vineet R Khare ,  Rahul Chougule

Inventor： Dnyanesh Rajpathak ,  Vineet R Khare ,  Rahul Chougule

IPC: G06F17/30

CPC classification number: G06F17/2785 ,  G10L15/1822

Abstract: A document may be received at a processing module. One or more tags may be applied to the document, each tag applied to a term, each tag representing a part of speech. One or more terms may be extracted from the document based on the tag. A weighting assignment parameter may be determined for each of the one or more extracted terms. Based on the weighting assignment parameter associated with each of the extracted terms, it may be determined whether the domain ontology includes the one or more extracted terms. If the domain ontology does not include the one or more extracted terms, the domain ontology may be augmented such that the domain ontology comprises the one or more extracted terms.

Abstract translation: 可以在处理模块处接收文档。 可以将一个或多个标签应用于文档，每个标签应用于术语，每个标签表示一部分语音。 可以基于标签从文档中提取一个或多个术语。 可以针对所提取的一个或多个术语中的每一个确定加权分配参数。 基于与所提取的每个项相关联的加权分配参数，可以确定域本体是否包括一个或多个提取的项。 如果域本体不包括一个或多个提取的术语，则域本体可以被扩充，使得域本体包括一个或多个提取的术语。

公开(公告)号：US08489601B2

公开(公告)日：2013-07-16

申请号：US12832142

申请日：2010-07-08

Applicant: Dnyanesh Rajpathak

Inventor： Dnyanesh Rajpathak

IPC: G06F17/30

CPC classification number: G06F17/3071 ,  G06Q10/20

Abstract: A method for extracting data from service repair verbatims in a vehicle service reporting system. Each service repair verbatim includes a technician's comments concerning a part, a symptom associated with the part, and a repair action associated with the symptom. Each service repair verbatim includes information relating to an identified problem with at least one vehicle part. A diagnostic and prognostic ontology database is provided that is structured by vehicle part classification, a vehicle part sub-class classification, and a relationship classification, wherein the relationship classification includes symptom relationships and action relationships. Each of the service repair verbatims are reconstructed utilizing the diagnostic and prognostic ontology database. Combinations of information are extracted from the reconstructed service repair verbatims as a function of user input criteria. A frequency is determined of each combination extracted in the reconstructed service repair verbatims. The service repair verbatims are clustered for each combination.

Abstract translation: 一种在车辆服务报告系统中从维修服务修复中提取数据的方法。 每次服务维修逐字包括技术人员对部分的意见，与该部分相关的症状以及与症状相关的修复动作。 每个服务维修逐字地包括与至少一个车辆部件的识别问题有关的信息。 提供了一种诊断和预测本体数据库，其由车辆部件分类，车辆部件子类别分类和关系分类构成，其中关系分类包括症状关系和动作关系。 使用诊断和预测本体数据库重建每个维修服务修复程序。 信息的组合作为用户输入标准的函数从重建的服务修复中提取出来。 确定在重建服务修复中提取的每个组合的频率。 针对每个组合，对服务修复逐字节进行聚类。

公开(公告)号：US08452774B2

公开(公告)日：2013-05-28

申请号：US13044873

申请日：2011-03-10

Applicant: Dnyanesh Rajpathak

Inventor： Dnyanesh Rajpathak

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30734 ,  G06F17/2795

Abstract: A method and system for splitting a text document into individual sentences using sentence boundary detection, and establishing co-relationships between terms which are present in the same sentence. A document corpus, or collection of text records, is provided, containing text with terms to be extracted. The text records in the document corpus are divided into individual sentences, using a set of rules for sentence boundary detection. The individual sentences are then analyzed to extract and correlate terms, such as parts and symptoms, symptoms and actions, or parts and failure modes. The correlated terms are then validated based on frequency of occurrence, with term pairs being considered valid if their frequency of occurrence exceeds a minimum frequency threshold. The validated term correlations can be used for fault model development, document classification, and document clustering.

Abstract translation: 一种使用句子边界检测将文本文档分割成单个句子的方法和系统，并且在同一句子中存在的术语之间建立共同关系。 提供文档语料库或文本记录集合，其中包含要提取的术语的文本。 文档语料库中的文本记录被分为单独的句子，使用一组用于句子边界检测的规则。 然后分析单个句子以提取和关联术语，如部分和症状，症状和动作，或部分和失败模式。 然后根据出现频率对相关项进行验证，如果出现的频率超过最小频率阈值，则术语对被认为是有效的。 验证的术语相关性可用于故障模型开发，文档分类和文档聚类。

公开(公告)号：US20120011073A1

公开(公告)日：2012-01-12

申请号：US12832142

申请日：2010-07-08

Applicant: Dnyanesh Rajpathak

Inventor： Dnyanesh Rajpathak

IPC: G06Q10/00 ,  G06F17/30

CPC classification number: G06F17/3071 ,  G06Q10/20

Abstract: A method is provided for extracting data from service repair verbatims in a vehicle service reporting system. Each service repair verbatim includes a technician's comments concerning a part, a symptom associated with the part, and a repair action associated with the symptom. Each service repair verbatim includes information relating to an identified problem with at least one vehicle part. A diagnostic and prognostic ontology database is provided that is structured by vehicle part classification, a vehicle part sub-class classification, and a relationship classification, wherein the relationship classification includes symptom relationships and action relationships. Each of the service repair verbatims are reconstructed utilizing the diagnostic and prognostic ontology database. Combinations of information are extracted from the reconstructed service repair verbatims as a function of user input criteria. A frequency is determined of each combination extracted in the reconstructed service repair verbatims. The service repair verbatims are clustered for each combination.

Abstract translation: 提供一种用于从车辆服务报告系统中的服务修复逐字逐句提取数据的方法。 每次服务维修逐字包括技术人员对部分的意见，与该部分相关的症状以及与症状相关的修复动作。 每个服务维修逐字地包括与至少一个车辆部件的识别问题有关的信息。 提供了一种诊断和预测本体数据库，其由车辆部件分类，车辆部件子类别分类和关系分类构成，其中关系分类包括症状关系和动作关系。 使用诊断和预测本体数据库重建每个维修服务修复程序。 信息的组合作为用户输入标准的函数从重建的服务修复中提取出来。 确定在重建服务修复中提取的每个组合的频率。 对于每个组合，对服务修复逐字节进行聚类。