公开(公告)号：US09098575B2

公开(公告)日：2015-08-04

申请号：US13527914

申请日：2012-06-20

申请人： Ihab Francis Ilyas ,  Mohamed A. Soliman ,  Peter Joseph Sweeney

发明人： Ihab Francis Ilyas ,  Mohamed A. Soliman ,  Peter Joseph Sweeney

IPC分类号： G06F17/30

CPC分类号： G06F17/30867 ,  G06F17/3053 ,  G06F17/30731

摘要： Techniques for specifying user preferences in a semantic network. The techniques include receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user's preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user's preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

摘要翻译： 用于在语义网络中指定用户偏好的技术。 所述技术包括：在语义网络中接收使用至少一个处理器中的至少一个概念的多个一阶用户偏好，其中所述多个一阶用户偏好指示所述用户在所述第 语义网络中至少有一个概念; 使用所述至少一个处理器接收所述语义网络中的所述至少一个概念的至少一个二阶用户偏好，其中所述至少一个二阶用户偏好指示所述至少一个以上的属性中的所述用户的偏好 一个概念; 以及通过使用所述语义网络，所述多个一阶用户偏好以及所述至少一个二阶用户偏好来执行至少一个语义处理动作。

公开(公告)号：US20120323899A1

公开(公告)日：2012-12-20

申请号：US13527914

申请日：2012-06-20

申请人： Ihab Francis Ilyas ,  Mohamed A. Soliman ,  Peter Joseph Sweeney

发明人： Ihab Francis Ilyas ,  Mohamed A. Soliman ,  Peter Joseph Sweeney

IPC分类号： G06F17/30

CPC分类号： G06F17/30867 ,  G06F17/3053 ,  G06F17/30731

摘要： Techniques for specifying user preferences in a semantic network. The techniques include receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user's preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user's preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

摘要翻译： 用于在语义网络中指定用户偏好的技术。 所述技术包括：在语义网络中接收使用至少一个处理器中的至少一个概念的多个一阶用户偏好，其中所述多个一阶用户偏好指示所述用户在所述第 语义网络中至少有一个概念; 使用所述至少一个处理器接收所述语义网络中的所述至少一个概念的至少一个二阶用户偏好，其中所述至少一个二阶用户偏好指示所述至少一个以上的属性中的所述用户的偏好 一个概念; 以及通过使用所述语义网络，所述多个一阶用户偏好以及所述至少一个二阶用户偏好来执行至少一个语义处理动作。

公开(公告)号：US20120166371A1

公开(公告)日：2012-06-28

申请号：US13345637

申请日：2012-01-06

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

IPC分类号： G06F15/18

CPC分类号： G06N5/02 ,  G06F16/84 ,  G06N7/005

摘要： Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may depend on user models, context information, preference information, and/or preference models.

摘要翻译： 用于分析和合成复杂知识表示（KR）的技术可以利用原子知识表示模型，其包括存储为机器可读数据和/或编程指令的元数据结构和知识处理规则。 可以应用知识处理规则中的一个或多个来分析输入复合体KR以将其复杂概念和/或概念关系解构为要包括在基本数据结构中的元素概念和/或概念关系。 知识处理规则中的一个或多个可以应用于根据上下文信息从所存储的基本数据结构合成输出复合体KR。 填充元素数据结构的方法和从元素数据结构合成复合KR的方法可以取决于用户模型，上下文信息，偏好信息和/或偏好模型。

公开(公告)号：US20110320396A1

公开(公告)日：2011-12-29

申请号：US13165423

申请日：2011-06-21

申请人： Anne Jude Hunt ,  Alexander David Black ,  Peter Joseph Sweeney ,  Ihab Francis Ilyas

发明人： Anne Jude Hunt ,  Alexander David Black ,  Peter Joseph Sweeney ,  Ihab Francis Ilyas

IPC分类号： G06N5/02

CPC分类号： G06N5/02 ,  G06F17/30914

摘要： Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with an input context. Multiple input complex KRs of various types may be analyzed and deconstructed to populate the elemental data structure, and input complex KRs may be transformed through the elemental data structure to output complex KRs of different types, providing semantic interoperability to KRs of different types and/or KR models.

摘要翻译： 用于分析和合成复杂知识表示（KR）的技术可以利用原子知识表示模型，其包括存储为机器可读数据和/或编程指令的元数据结构和知识处理规则。 可以应用知识处理规则中的一个或多个来分析输入复合体KR以将其复杂概念和/或概念关系解构为要包括在基本数据结构中的元素概念和/或概念关系。 一个或多个知识处理规则可以被应用以根据输入上下文从存储的基本数据结构合成输出复合体KR。 可以对各种类型的多输入复合体KR进行分析和解构以填充元素数据结构，并且可以通过元素数据结构来转换输入复数KR，以输出不同类型的复合KR，为不同类型和/或不同类型的KR提供语义互操作性 KR型号。

公开(公告)号：US08676732B2

公开(公告)日：2014-03-18

申请号：US13340820

申请日：2011-12-30

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Jean-Paul Dupuis ,  Nadiya Yampolska

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Jean-Paul Dupuis ,  Nadiya Yampolska

IPC分类号： G06N5/00

CPC分类号： G06F17/30867

摘要： Methods and system of searching for content in a target set of content based on a reference set of content, a reference semantic network representing knowledge associated with the reference set of content, and a target semantic network representing knowledge associated with the target set of content. Techniques include receiving a user-specified search query, obtaining at least one concept semantically relevant to the user-specified search query by using the target semantic network and the reference semantic network, constructing a second query by augmenting the first search query with one or more terms associated with the at least one obtained concept; providing, to the at least one user, content associated with search results obtained based on searching the target set of content by using the second query, wherein any concept in the semantic network is represented by a data structure storing data associated with a node in the semantic network.

摘要翻译： 基于内容的参考集合来搜索目标内容集合中的内容的方法和系统，表示与所述参考内容集相关联的知识的参考语义网络，以及表示与所述目标内容集合相关联的知识的目标语义网络。 技术包括接收用户指定的搜索查询，通过使用目标语义网络和参考语义网络来获得与用户指定的搜索查询语义相关的至少一个概念，通过用一个或多个来扩充第一搜索查询来构建第二查询 与所述至少一个获得的概念相关联的术语; 向所述至少一个用户提供与基于通过使用所述第二查询搜索所述目标内容集合获得的搜索结果相关联的内容，其中所述语义网络中的任何概念由存储与所述第二查询中的节点相关联的数据的数据结构来表示 语义网络

公开(公告)号：US20120150874A1

公开(公告)日：2012-06-14

申请号：US13340792

申请日：2011-12-30

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Jean-Paul Dupuis ,  Nadiya Yampolska

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Jean-Paul Dupuis ,  Nadiya Yampolska

IPC分类号： G06F17/30 ,  G06Q30/02

CPC分类号： G06N5/02 ,  G06F17/2785 ,  G06F17/30528 ,  G06F17/30663 ,  G06F17/30684 ,  G06F17/30734 ,  G06N5/022 ,  G06Q30/0241 ,  G06Q30/0269

摘要： Methods and system for providing information selected from a large set of digital content to at least one user. One such method comprises receiving user context information associated with the at least one user and identifying or generating, using at least one processor executing stored program instructions, a first concept in a semantic network, the first concept representing at least a portion of the user context information. The method further comprises obtaining at least one concept, including a second concept, semantically relevant to the first concept at least in part, by synthesizing the second concept based on the first concept and at least one other concept in the semantic network; and providing information to the at least one user, wherein the information is selected by using the first concept and the at least one obtained concept semantically relevant to the first concept, wherein the first concept in a semantic network is represented by a data structure storing any data associated with a node in the semantic network.

摘要翻译： 用于向至少一个用户提供从大量数字内容中选择的信息的方法和系统。 一种这样的方法包括接收与至少一个用户相关联的用户上下文信息，并使用执行存储的程序指令的至少一个处理器识别或生成语义网络中的第一概念，第一概念表示用户上下文的至少一部分 信息。 所述方法还包括至少部分地通过基于所述第一概念和所述语义网络中的至少一个其他概念来合成所述第二概念来获得包括第二概念的至少一个概念，所述第二概念与所述第一概念语义相关; 以及向所述至少一个用户提供信息，其中通过使用所述第一概念和所述至少一个获得的与所述第一概念语义相关的概念来选择所述信息，其中语义网络中的所述第一概念由存储任何 与语义网络中的节点相关联的数据。

公开(公告)号：US10002325B2

公开(公告)日：2018-06-19

申请号：US13345644

申请日：2012-01-06

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Wu Zhou ,  Wayne Oldford

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas ,  Wu Zhou ,  Wayne Oldford

IPC分类号： G06F7/00 ,  G06F17/30 ,  G06N5/02 ,  G06N7/00

CPC分类号： G06N5/02 ,  G06F16/84 ,  G06N7/005

摘要： Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may rely on linguistic inference rules and/or elemental inference rules.

公开(公告)号：US20130066823A1

公开(公告)日：2013-03-14

申请号：US13609218

申请日：2012-09-10

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

IPC分类号： G06N5/02

CPC分类号： G06N5/02 ,  G06F16/3344 ,  G06N7/005

摘要： Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively.A method of constructing an elemental data structure may include analyzing first information to identify a first elemental component associated with a data consumer, and adding the first elemental component to a customized module corresponding to the data consumer. The method may also include analyzing second information to identify a second elemental component associated with a population, and adding the second elemental component to the universal kernel.

摘要翻译： 用于分析和合成复杂知识表示（KR）的技术可以利用包括机器可读的元素数据结构和知识处理规则的原子知识表示模型。 元素数据结构可以包括通用内核和定制模块，其可以分别表示通常适用于群体的知识和专门适用于个人数据消费者的知识。 构成元数据结构的方法可以包括分析第一信息以识别与数据消费者相关联的第一元素组件，以及将第一元素组件添加到与数据消费者对应的定制模块中。 该方法还可以包括分析第二信息以识别与群体相关联的第二元素分量，以及将第二元素分量添加到通用内核。

公开(公告)号：US20130060785A1

公开(公告)日：2013-03-07

申请号：US13609223

申请日：2012-09-10

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

IPC分类号： G06F17/30

CPC分类号： G06N5/02 ,  G06F17/30684 ,  G06N5/00 ,  G06N7/005

摘要： Techniques for analyzing and synthesizing complex knowledge representations may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. The elemental data structure may include a universal kernel and one or more customized modules. The universal kernel may represent knowledge that is generally applicable to a population, and the customized modules may represent knowledge that is specifically applicable to individual data consumers.Crowd-sourcing techniques may be applied to the elemental data structure. A method of modifying the elemental data structure may include obtaining an indicator regarding an elemental component based on data associated with customized modules. The method may further include determining whether the indicator satisfies a criterion for performing a modification operation on the elemental data structure, and, based on the indicator satisfying the criterion, performing the modification operation on the elemental computer data structure.

摘要翻译： 用于分析和合成复杂知识表示的技术可以利用包含作为机器可读数据和/或编程指令存储的基本数据结构和知识处理规则的原子知识表示模型。 基本数据结构可以包括通用内核和一个或多个定制模块。 通用内核可以表示通常适用于人口的知识，并且定制的模块可以表示专门适用于个人数据消费者的知识。 人群采集技术可以应用于元素数据结构。 修改元素数据结构的方法可以包括基于与定制模块相关联的数据获得关于元素分量的指标。 该方法还可以包括确定指示符是否满足用于对基本数据结构执行修改操作的标准，并且基于满足该标准的指标，对元素计算机数据结构进行修改操作。

公开(公告)号：US20130046723A1

公开(公告)日：2013-02-21

申请号：US13609225

申请日：2012-09-10

申请人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

发明人： Peter Joseph Sweeney ,  Ihab Francis Ilyas

IPC分类号： G06N5/02

CPC分类号： G06N5/02 ,  G06F8/24 ,  G06F16/3344 ,  G06F16/951 ,  G06N7/005

摘要： Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively.A method of outputting a complex KR may include receiving input from a data consumer. The method may further include applying rules to the elemental data structure. Applying rules to the elemental data structure may include applying a rule to the universal kernel and applying a rule to a customized module. The method may further include synthesizing a concept and/or a relationship based on the application of the rules, and outputting a complex KR that is customized to the data consumer based on the customized module.

摘要翻译： 用于分析和合成复杂知识表示（KR）的技术可以利用包括机器可读的元素数据结构和知识处理规则的原子知识表示模型。 元素数据结构可以包括通用内核和定制模块，其可以分别表示通常适用于群体的知识和专门适用于个人数据消费者的知识。 输出复合KR的方法可以包括从数据消费者接收输入。 该方法还可以包括将规则应用于元素数据结构。 将规则应用于元素数据结构可以包括将规则应用于通用内核并将规则应用于定制模块。 该方法还可以包括基于规则的应用来合成概念和/或关系，并且基于定制模块输出被定制到数据消费者的复合体KR。