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1. 发明授权

US09508038B2 Using ontological information in open domain type coercion 有权
标题翻译：使用开放域类型胁迫的本体信息
公开(公告)号：US09508038B2
公开(公告)日：2016-11-29
申请号：US13605339
申请日：2012-09-06
申请人： David A. Ferrucci , Aditya Kalyanpur , James W. Murdock, IV , Christopher A. Welty , Wlodek W. Zadrozny
发明人： David A. Ferrucci , Aditya Kalyanpur , James W. Murdock, IV , Christopher A. Welty , Wlodek W. Zadrozny
IPC分类号： G06F7/00 , G06N5/02
CPC分类号： G06N5/02 , G06F17/30654
摘要： A computer-implemented system, method and program product generates answers to questions in an input query text string. The method includes determining, by a programmed processor unit, a lexical answer type (LAT) string associated with an input query; automatically obtaining a candidate answer string to the input query from a data corpus; mapping the query LAT string to a first type string in a structured resource; mapping the candidate answer string to a second type string in the structured resource; and determining if the first type string and the second type string are disjointed; and scoring the candidate answer string based on the determination of the types being disjointed wherein the structured resource includes a semantic database providing ontological content.
摘要翻译：计算机实现的系统，方法和程序产品会在输入查询文本字符串中生成问题的答案。该方法包括由编程的处理器单元确定与输入查询相关联的词汇答案类型（LAT）字符串; 从数据语料库自动获得候选答案字符串到输入查询; 将查询LAT字符串映射到结构化资源中的第一个类型的字符串; 将候选答案字符串映射到结构化资源中的第二类型字符串; 以及确定所述第一类型字符串和所述第二类型字符串是否脱离; 以及基于所述不相交类型的确定对所述候选答案字符串进行评分，其中所述结构化资源包括提供本体内容的语义数据库。

2. 发明授权

US09361579B2 Large scale probabilistic ontology reasoning 有权
标题翻译：大规模概率本体推理
公开(公告)号：US09361579B2
公开(公告)日：2016-06-07
申请号：US12574237
申请日：2009-10-06
申请人： Achille B. Fokoue-Nkoutche , Aditya Kalyanpur , Edith G. Schonberg , Kavitha Srinivas
发明人： Achille B. Fokoue-Nkoutche , Aditya Kalyanpur , Edith G. Schonberg , Kavitha Srinivas
IPC分类号： G06N5/02 , G06N7/00
CPC分类号： G06N5/02 , G06N7/005
摘要： Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.
摘要翻译：提供了用于计算针对知识库（KB）制定的查询的解决方案的技术。这些技术包括接收针对知识库制定的查询，其中所述知识库包括一组一个或多个公理，其中每个公理用指示分配给其的确定程度的特定概率值进行注释，忽略该概率值的一个概率值或更多的公理，并计算查询的解决方案，计算查询解决方案的一个或多个理由中的每一个，其中计算查询解决方案的一个或多个理由中的每一个包括确定知识库中的一个或多个公理的最小集合，需要查询解决方案，并使用每个对齐中的一个或多个公理的每个概率值来计算推断的查询解的净概率。

3. 发明授权

US09037615B2 Querying and integrating structured and unstructured data 有权
标题翻译：查询和整合结构化和非结构化数据
公开(公告)号：US09037615B2
公开(公告)日：2015-05-19
申请号：US13493174
申请日：2012-06-11
申请人： Mihaela Ancuta Bornea , Songyun Duan , James J. Fan , Achille Fokoue-Nkoutche , Alfio M. Gliozzo , Aditya Kalyanpur , Anastasios Kementsietsidis , Kavitha Srinivas , Michael J. Ward
发明人： Mihaela Ancuta Bornea , Songyun Duan , James J. Fan , Achille Fokoue-Nkoutche , Alfio M. Gliozzo , Aditya Kalyanpur , Anastasios Kementsietsidis , Kavitha Srinivas , Michael J. Ward
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30946 , G06F17/30292
摘要： A computer-implemented method, system, and article of manufacture for querying and integrating structured and unstructured data. The method includes: receiving entity information that is extracted from a first set of unstructured data using an open domain information extraction system, wherein the entity in-formation comprises relationship information between a first entity and a second entity of the first set of unstructured data; recognizing a pattern based on the relationship information and creating a schema for the first set of unstructured data based on the pattern; and associating an element of the created schema with (i) an entity of a second set of unstructured data or (ii) a schema element of an existing set of structured data if there is sufficient overall similarity between the created schema element and either the second unstructured data entity or the schema element of the existing structured data.
摘要翻译：用于查询和整合结构化和非结构化数据的计算机实现的方法，系统和制造。该方法包括：使用开放域信息提取系统接收从第一组非结构化数据提取的实体信息，其中所述实体信息包括第一组非结构化数据的第一实体与第二实体之间的关系信息; 基于所述关系信息识别模式，并基于所述模式为所述第一组非结构化数据创建模式; 并且将所创建的模式的元素与（i）第二组非结构化数据的实体相关联，或者（ii）现有结构化数据集合的模式元素，如果所创建的模式元素与第二组之间存在足够的总体相似度非结构化数据实体或现有结构化数据的架构元素。

4. 发明申请

US20130332478A1 QUERYING AND INTEGRATING STRUCTURED AND INSTRUCTURED DATA 有权
标题翻译：查询和整合结构化和结构化数据
公开(公告)号：US20130332478A1
公开(公告)日：2013-12-12
申请号：US13493174
申请日：2012-06-11
申请人： Mihaela Ancuta Bornea , Songyun Duan , James J. Fan , Achille Fokoue-Nkoutche , Alfio M. Gliozzo , Aditya Kalyanpur , Anastasios Kementsietsidis , Kavitha Srinivas , Michael J. Ward
发明人： Mihaela Ancuta Bornea , Songyun Duan , James J. Fan , Achille Fokoue-Nkoutche , Alfio M. Gliozzo , Aditya Kalyanpur , Anastasios Kementsietsidis , Kavitha Srinivas , Michael J. Ward
IPC分类号： G06F17/30
CPC分类号： G06F17/30946 , G06F17/30292
摘要： A computer-implemented method, system, and article of manufacture for querying and integrating structured and unstructured data. The method includes: receiving entity information that is extracted from a first set of unstructured data using an open domain information extraction system, wherein the entity information comprises relationship information between a first entity and a second entity of the first set of unstructured data; recognizing a pattern based on the relationship information and creating a schema for the first set of unstructured data based on the pattern; and associating an element of the created schema with (i) an entity of a second set of unstructured data or (ii) a schema element of an existing set of structured data if there is sufficient overall similarity between the created schema element and either the second unstructured data entity or the schema element of the existing structured data.
摘要翻译：用于查询和整合结构化和非结构化数据的计算机实现的方法，系统和制造。该方法包括：使用开放域信息提取系统接收从第一组非结构化数据提取的实体信息，其中实体信息包括第一组非结构化数据的第一实体与第二实体之间的关系信息; 基于所述关系信息识别模式，并基于所述模式为所述第一组非结构化数据创建模式; 并且将所创建的模式的元素与（i）第二组非结构化数据的实体相关联，或者（ii）现有结构化数据集合的模式元素，如果所创建的模式元素与第二组之间存在足够的总体相似度非结构化数据实体或现有结构化数据的架构元素。

5. 发明申请

US20070233627A1 Scalable ontology reasoning 有权
标题翻译：可扩展本体推理
公开(公告)号：US20070233627A1
公开(公告)日：2007-10-04
申请号：US11708949
申请日：2007-02-21
申请人： Julian Dolby , Aditya Kalyanpur , Aaron Jay Kershenbaum , Achille Fokoue-Nkoutche , Li Ma , Edith Schonberg , Kavitha Srinivas
发明人： Julian Dolby , Aditya Kalyanpur , Aaron Jay Kershenbaum , Achille Fokoue-Nkoutche , Li Ma , Edith Schonberg , Kavitha Srinivas
IPC分类号： G06N5/00
CPC分类号： G06N5/02 , G06N5/00
摘要： Methods and apparatus, including computer program products, for scalable ontology reasoning. A method of generating a summarized ontology includes loading an ontology from a store, eliminating relationships in the ontology, the eliminating relationships including an insertion of new relationships that simplify the ontology, eliminating individuals in the ontology, the eliminating individuals including insertion of new individuals to simplify the ontology, eliminating concepts in the ontology including insertion of new concepts to simplify the ontology, and generating the summarized ontology from the eliminating relationships, eliminating individuals and eliminating concepts.
摘要翻译：方法和设备，包括计算机程序产品，用于可扩展本体推理。生成总结本体的方法包括从商店加载本体，消除本体中的关系，消除关系，包括插入简化本体的新关系，消除本体中的个体，消除个体，包括插入新个体简化本体，消除本体中的概念，包括插入新概念以简化本体，并从消除关系，消除个人和消除概念生成摘要本体。

6. 发明授权

US08538904B2 Scalable ontology extraction 有权
标题翻译：可扩展本体提取
公开(公告)号：US08538904B2
公开(公告)日：2013-09-17
申请号：US12916779
申请日：2010-11-01
申请人： Achille Fokoue , Aditya Kalyanpur , Kavitha Srinivas
发明人： Achille Fokoue , Aditya Kalyanpur , Kavitha Srinivas
IPC分类号： G06N5/04
CPC分类号： G06N5/025 , G06F19/00
摘要： A system and computer program product for facilitating learning of one or more ontological rules of a resource description framework database include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.
摘要翻译：用于促进对资源描述框架数据库的一个或多个本体论规则的学习的系统和计算机程序产品包括从资源描述框架数据库获得本体词汇，通过以下方式逐渐建立基于先前学习的规则的数据库生成规则假设：或更多的谓词，通过确定与每个先前学习的规则的兼容性来执行对生成的规则假设的约束检查，以确保包括每个先前学习的规则和生成的规则假设的完整规则集是一致的，验证规则假设作为规则，使用一个或多个关联规则挖掘技术来确定针对数据库的规则假设的有效性，以及将规则应用于数据库以从数据库推断一个或多个事实，以便于学习一个或多个附加本体规则。

7. 发明申请

US20120109859A1 Scalable Ontology Extraction 有权
标题翻译：可扩展本体抽取
公开(公告)号：US20120109859A1
公开(公告)日：2012-05-03
申请号：US12916779
申请日：2010-11-01
申请人： Achille Fokoue , Aditya Kalyanpur , Kavitha Srinivas
发明人： Achille Fokoue , Aditya Kalyanpur , Kavitha Srinivas
IPC分类号： G06F15/18 , G06N5/04
CPC分类号： G06N5/025 , G06F19/00
摘要： Techniques for facilitating learning of one or more ontological rules of a resource description framework database are provided. The techniques include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.
摘要翻译：提供了一种便于学习资源描述框架数据库的一个或多个本体论规则的技术。这些技术包括从资源描述框架数据库中获取本体词汇，通过向先前学习的规则添加一个或多个谓词，通过逐步建立在先前学习的规则上，从数据库生成规则假设，通过以下方式对生成的规则假设执行约束检查：确定与每个先前学习的规则的兼容性，以确保包括每个先前学习的规则和生成的规则假设的完整规则集合是一致的，使用一个或多个关联规则挖掘技术来将规则假设作为规则验证，以确定规则假设的有效性数据库，以及将规则应用于数据库以从数据库推断一个或多个事实，以便于学习一个或多个附加本体规则。

8. 发明申请

US20110082828A1 Large Scale Probabilistic Ontology Reasoning 有权
标题翻译：大规模概率本体论推理
公开(公告)号：US20110082828A1
公开(公告)日：2011-04-07
申请号：US12574237
申请日：2009-10-06
申请人： Achille B. Fokoue-Nkoutche , Aditya Kalyanpur , Edith G. Schonberg , Kavitha Srinivas
发明人： Achille B. Fokoue-Nkoutche , Aditya Kalyanpur , Edith G. Schonberg , Kavitha Srinivas
IPC分类号： G06N5/02
CPC分类号： G06N5/02 , G06N7/005
摘要： Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.
摘要翻译：提供了用于计算针对知识库（KB）制定的查询的解决方案的技术。这些技术包括接收针对知识库制定的查询，其中所述知识库包括一组一个或多个公理，其中每个公理用指示分配给其的确定程度的特定概率值进行注释，忽略该概率值的一个概率值或更多的公理，并计算查询的解决方案，计算查询解决方案的一个或多个理由中的每一个，其中计算查询解决方案的一个或多个理由中的每一个包括确定知识库中的一个或多个公理的最小集合，需要查询解决方案，并使用每个对齐中的一个或多个公理的每个概率值来计算推断的查询解的净概率。

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