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1. 发明授权

US07529974B2 Grouping failures to infer common causes 有权
标题翻译：分组失败来推断常见原因
公开(公告)号：US07529974B2
公开(公告)日：2009-05-05
申请号：US11565538
申请日：2006-11-30
申请人： Romain Thibaux , Emre Kiciman , David A. Maltz
发明人： Romain Thibaux , Emre Kiciman , David A. Maltz
IPC分类号： G06F11/00
CPC分类号： G06Q10/04
摘要： Systems and methods establish groups among numerous indications of failure in order to infer a cause of failure common to each group. In one implementation, a system computes the groups such that each group has the maximum likelihood of resulting from a common failure. Indications of failure are grouped by probability, even when a group's inferred cause of failure is not directly observable in the system. In one implementation, related matrices provide a system for receiving numerous health indications from each of numerous autonomous systems connected with the Internet. A correlational matrix links input (failure symptoms) and output (known or unknown root causes) through probability-based hypothetical groupings of the failure indications. The matrices are iteratively refined according to self-consistency and parsimony metrics to provide most likely groupings of indicators and most likely causes of failure.
摘要翻译：系统和方法在众多的失败迹象中建立了群体，以便推断每个群体共同的失败原因。在一个实现中，系统计算组，使得每个组具有由于共同失败而导致的最大可能性。失败的指示按概率分组，即使一组的推断的故障原因在系统中不能直接观察到。在一个实现中，相关矩阵提供用于从与互联网连接的许多自主系统中的每一个接收许多健康指示的系统。相关矩阵通过故障指示的基于概率的假设分组来连接输入（故障症状）和输出（已知或未知的根本原因）。矩阵根据自我一致性和简约度量进行迭代改进，以提供最可能的指标分组和最可能的故障原因。

2. 发明申请

US20120323839A1 ENTITY RECOGNITION USING PROBABILITIES FOR OUT-OF-COLLECTION DATA 有权
标题翻译：使用无法收集数据的概率的实体识别
公开(公告)号：US20120323839A1
公开(公告)日：2012-12-20
申请号：US13162563
申请日：2011-06-16
申请人： Emre Kiciman , Abulimiti Aji , Kuansan Wang
发明人： Emre Kiciman , Abulimiti Aji , Kuansan Wang
IPC分类号： G06N5/02
CPC分类号： G06N99/005
摘要： A classifier that disambiguates among entities based on a dictionary, such as corpus of documents about those entities, is built by incorporating probabilities that an entity exists that is not in the dictionary. Given a document it is associated by the classifier with an entity. By incorporating out of collection probabilities into the classifier, a higher level of confidence in the match between an entity and a document is achieved.
摘要翻译：基于字典的实体之间消歧的分类器，例如关于这些实体的文档语料库，是通过并入不在字典中的实体存在的概率来构建的。给定一个文档，它由分类器与实体相关联。通过将收集概率合并到分类器中，实现了实体和文档之间的匹配的更高的置信度。

3. 发明申请

US20120158668A1 STRUCTURING UNSTRUCTURED WEB DATA USING CROWDSOURCING 有权
标题翻译：使用CROWDSOURCING结构化非WEB网络数据
公开(公告)号：US20120158668A1
公开(公告)日：2012-06-21
申请号：US12971976
申请日：2010-12-17
申请人： Yi-Chin Tu , Aleksey Sinyagin , Xiaoxin Yin , Wenzhao Tan , Li-wei He , Yi-Min Wang , Emre Kiciman , Chun-Kai Wang
发明人： Yi-Chin Tu , Aleksey Sinyagin , Xiaoxin Yin , Wenzhao Tan , Li-wei He , Yi-Min Wang , Emre Kiciman , Chun-Kai Wang
IPC分类号： G06F17/30
CPC分类号： G06Q10/101 , G06F17/30882
摘要： A crowdsourcing data structuring system and method for capturing unstructured data from the Web and adding structure by placing the data in a document that is accessible by others in a cloud computing environment. Using crowdsourcing, the unstructured data is annotated, amended, and verified to add structure to the unstructured data. An anchor and update module convert the data to a pointer that links the document to the data at an information source and stores the pointer in the document rather than the data itself. The data displayed in the document is updated whenever the information source is updated. A contribution module allows users to add data to the document, a validation module allows users to determine the validity of the data linked to in the document, and an expert ranking module allows users to rank the expert or contributor of the data in the document.
摘要翻译：用于从Web获取非结构化数据并通过将数据放置在可由其他人在云计算环境中访问的文档中来添加结构的众包数据结构化系统和方法。使用众包，非结构化数据进行注释，修改和验证，以向非结构化数据添加结构。锚和更新模块将数据转换为将文档链接到信息源上的数据的指针，并将指针存储在文档中而不是数据本身。每当更新信息源时，文档中显示的数据都会更新。贡献模块允许用户向文档添加数据，验证模块允许用户确定文档中链接的数据的有效性，专家排名模块允许用户对文档中的数据的专家或贡献者进行排名。

4. 发明授权

US09104979B2 Entity recognition using probabilities for out-of-collection data 有权
标题翻译：使用不合规数据的概率进行实体识别
公开(公告)号：US09104979B2
公开(公告)日：2015-08-11
申请号：US13162563
申请日：2011-06-16
申请人： Emre Kiciman , Abulimiti Aji , Kuansan Wang
发明人： Emre Kiciman , Abulimiti Aji , Kuansan Wang
IPC分类号： G06F15/18 , G06N99/00
CPC分类号： G06N99/005
摘要： A classifier that disambiguates among entities based on a dictionary, such as corpus of documents about those entities, is built by incorporating probabilities that an entity exists that is not in the dictionary. Given a document it is associated by the classifier with an entity. By incorporating out of collection probabilities into the classifier, a higher level of confidence in the match between an entity and a document is achieved.
摘要翻译：基于字典的实体之间消歧的分类器，例如关于这些实体的文档语料库，是通过并入不在字典中的实体存在的概率来构建的。给定一个文档，它由分类器与实体相关联。通过将收集概率合并到分类器中，实现了实体和文档之间的匹配的更高的置信度。

5. 发明授权

US09460419B2 Structuring unstructured web data using crowdsourcing 有权
标题翻译：使用众包构建非结构化Web数据
公开(公告)号：US09460419B2
公开(公告)日：2016-10-04
申请号：US12971976
申请日：2010-12-17
申请人： Yi-Chin Tu , Aleksey Sinyagin , Xiaoxin Yin , Wenzhao Tan , Li-wei He , Yi-Min Wang , Emre Kiciman , Chun-Kai Wang
发明人： Yi-Chin Tu , Aleksey Sinyagin , Xiaoxin Yin , Wenzhao Tan , Li-wei He , Yi-Min Wang , Emre Kiciman , Chun-Kai Wang
IPC分类号： G06F17/30 , G06Q10/10
CPC分类号： G06Q10/101 , G06F17/30882
摘要： A crowdsourcing data structuring system and method for capturing unstructured data from the Web and adding structure by placing the data in a document that is accessible by others in a cloud computing environment. Using crowdsourcing, the unstructured data is annotated, amended, and verified to add structure to the unstructured data. An anchor and update module convert the data to a pointer that links the document to the data at an information source and stores the pointer in the document rather than the data itself. The data displayed in the document is updated whenever the information source is updated. A contribution module allows users to add data to the document, a validation module allows users to determine the validity of the data linked to in the document, and an expert ranking module allows users to rank the expert or contributor of the data in the document.
摘要翻译：用于从Web获取非结构化数据并通过将数据放置在可由其他人在云计算环境中访问的文档中来添加结构的众包数据结构化系统和方法。使用众包，非结构化数据进行注释，修改和验证，以向非结构化数据添加结构。锚和更新模块将数据转换为将文档链接到信息源上的数据的指针，并将指针存储在文档中而不是数据本身。每当更新信息源时，文档中显示的数据都会更新。贡献模块允许用户向文档添加数据，验证模块允许用户确定文档中链接的数据的有效性，专家排名模块允许用户对文档中的数据的专家或贡献者进行排名。

6. 发明授权

US09405555B2 Automated code splitting and pre-fetching for improving responsiveness of browser-based applications 有权
标题翻译：自动代码分割和预取，以提高基于浏览器的应用程序的响应速度
公开(公告)号：US09405555B2
公开(公告)日：2016-08-02
申请号：US12125931
申请日：2008-05-23
申请人： Benjamin Livshits , Emre Kiciman , Chen Ding
发明人： Benjamin Livshits , Emre Kiciman , Chen Ding
IPC分类号： G06F9/44 , G06F9/54
CPC分类号： G06F9/451 , G06F9/547
摘要： A “code splitting tool” provides various techniques for automatically analyzing and rewriting existing browser-based applications to introduce dynamic code loading into those applications thereby improving perceived application responsiveness. Structural elements of application code (including functions, classes, etc.) are broken into small “stubs” with corresponding bodies. Rewritten applications then initially transfer only the portion of the code (including some combination of stubs and bodies) to the client as necessary for initial application execution. Additional stubs and/or bodies are then transferred either on-demand at runtime or in the background. Automated code rewriting proceeds without requiring any application-specific knowledge or changes to existing code prior to code rewriting. Further, the code splitting tool can tailor code rewriting to specific computing devices (computers, PDA's, cell phones, etc.), specific network conditions, and/or specific users, through an automated training process that creates clusters that control code downloads to optimize perceived application responsiveness.
摘要翻译： “代码分解工具”提供了各种自动分析和重写现有基于浏览器的应用程序的技术，以将动态代码加载到这些应用程序中，从而提高了应用程序的响应能力。应用代码（包括函数，类等）的结构元素被分解成与对应的主体的小的“存根”。然后，重写的应用程序最初只将代码的一部分（包括存根和主体的一些组合）传送到客户端，以便初始执行应用程序。然后在运行时或后台按需传递附加的存根和/或物体。自动代码重写在代码重写之前不需要任何特定于应用程序的知识或现有代码的更改。此外，代码分割工具可以通过创建控制代码下载以优化的集群的自动化培训过程来定制重写到特定计算设备（计算机，PDA，手机等），特定网络条件和/或特定用户的代码重写感知应用程序响应。

7. 发明申请

US20090292791A1 AUTOMATED CODE SPLITTING AND PRE-FETCHING FOR IMPROVING RESPONSIVENESS OF BROWSER-BASED APPLICATIONS 有权
标题翻译：用于改进基于浏览器的应用程序的自动化代码分割和预失效
公开(公告)号：US20090292791A1
公开(公告)日：2009-11-26
申请号：US12125931
申请日：2008-05-23
申请人： Benjamin Livshits , Emre Kiciman , Chen Ding
发明人： Benjamin Livshits , Emre Kiciman , Chen Ding
IPC分类号： G06F9/44 , G06F15/16
CPC分类号： G06F9/451 , G06F9/547
摘要： A “code splitting tool” provides various techniques for automatically analyzing and rewriting existing browser-based applications to introduce dynamic code loading into those applications thereby improving perceived application responsiveness. Structural elements of application code (including functions, classes, etc.) are broken into small “stubs” with corresponding bodies. Rewritten applications then initially transfer only the portion of the code (including some combination of stubs and bodies) to the client as necessary for initial application execution. Additional stubs and/or bodies are then transferred either on-demand at runtime or in the background. Automated code rewriting proceeds without requiring any application-specific knowledge or changes to existing code prior to code rewriting. Further, the code splitting tool can tailor code rewriting to specific computing devices (computers, PDA's, cell phones, etc.), specific network conditions, and/or specific users, through an automated training process that creates clusters that control code downloads to optimize perceived application responsiveness.
摘要翻译： “代码分解工具”提供了各种自动分析和重写现有基于浏览器的应用程序的技术，以将动态代码加载到这些应用程序中，从而提高了应用程序的响应能力。应用代码（包括函数，类等）的结构元素被分解成与对应的主体的小的“存根”。然后，重写的应用程序最初只将代码的一部分（包括存根和主体的一些组合）传送到客户端，以便初始执行应用程序。然后在运行时或后台按需传递附加的存根和/或物体。自动代码重写在代码重写之前不需要任何特定于应用程序的知识或现有代码的更改。此外，代码分割工具可以通过创建控制代码下载以优化的集群的自动化培训过程来定制重写到特定计算设备（计算机，PDA，手机等），特定网络条件和/或特定用户的代码重写感知应用程序响应。

8. 发明申请

US20080133288A1 Grouping Failures to Infer Common Causes 有权
标题翻译：分组故障导致常见原因
公开(公告)号：US20080133288A1
公开(公告)日：2008-06-05
申请号：US11565538
申请日：2006-11-30
申请人： Romain Thibaux , Emre Kiciman , David A. Maltz
发明人： Romain Thibaux , Emre Kiciman , David A. Maltz
IPC分类号： G06Q10/00
CPC分类号： G06Q10/04
摘要： Systems and methods establish groups among numerous indications of failure in order to infer a cause of failure common to each group. In one implementation, a system computes the groups such that each group has the maximum likelihood of resulting from a common failure. Indications of failure are grouped by probability, even when a group's inferred cause of failure is not directly observable in the system. In one implementation, related matrices provide a system for receiving numerous health indications from each of numerous autonomous systems connected with the Internet. A correlational matrix links input (failure symptoms) and output (known or unknown root causes) through probability-based hypothetical groupings of the failure indications. The matrices are iteratively refined according to self-consistency and parsimony metrics to provide most likely groupings of indicators and most likely causes of failure.
摘要翻译：系统和方法在众多的失败迹象中建立了群体，以便推断每个群体共同的失败原因。在一个实现中，系统计算组，使得每个组具有由于共同失败而导致的最大可能性。失败的指示按概率分组，即使一组的推断的故障原因在系统中不能直接观察到。在一个实现中，相关矩阵提供用于从与互联网连接的许多自主系统中的每一个接收许多健康指示的系统。相关矩阵通过故障指示的基于概率的假设分组来连接输入（故障症状）和输出（已知或未知的根本原因）。矩阵根据自我一致性和简约度量进行迭代改进，以提供最可能的指标分组和最可能的故障原因。

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