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1. 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。

2. 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。

3. 发明授权

US08041710B2 Automatic diagnosis of search relevance failures 有权
标题翻译：自动诊断搜索相关性故障
公开(公告)号：US08041710B2
公开(公告)日：2011-10-18
申请号：US12270201
申请日：2008-11-13
申请人： Li-wei He , Wenzhao Tan , Jinliang Fan , Yi-Min Wang , Xiaoxin Yin
发明人： Li-wei He , Wenzhao Tan , Jinliang Fan , Yi-Min Wang , Xiaoxin Yin
IPC分类号： G06F17/30
CPC分类号： G06F17/30867
摘要： Search relevance failures are diagnosed automatically. Users presented with unsatisfactory search results can report their dissatisfaction through various mechanisms. Dissatisfaction reports can trigger automatic investigation into the root cause of such dissatisfaction. Based on the identified root cause, a search engine can be modified to resolve the issue creating dissatisfaction thereby improving search engine quality.
摘要翻译：搜索相关性故障自动诊断。用户不满意的搜索结果可以通过各种机制报告他们的不满。不满意的报告可能引发自动调查，造成这种不满的根本原因。基于确定的根本原因，可以修改搜索引擎来解决创建不满意的问题，从而提高搜索引擎的质量。

4. 发明申请

US20100121841A1 AUTOMATIC DIAGNOSIS OF SEARCH RELEVANCE FAILURES 有权
标题翻译：搜索相关失败的自动诊断
公开(公告)号：US20100121841A1
公开(公告)日：2010-05-13
申请号：US12270201
申请日：2008-11-13
申请人： Li-wei He , Wenzhao Tan , Jinliang Fan , Yi-Min Wang , Xiaoxin Yin
发明人： Li-wei He , Wenzhao Tan , Jinliang Fan , Yi-Min Wang , Xiaoxin Yin
IPC分类号： G06F7/10 , G06F17/30 , G06N5/02
CPC分类号： G06F17/30867
摘要： Search relevance failures are diagnosed automatically. Users presented with unsatisfactory search results can report their dissatisfaction through various mechanisms. Dissatisfaction reports can trigger automatic investigation into the root cause of such dissatisfaction. Based on the identified root cause, a search engine can be modified to resolve the issue creating dissatisfaction thereby improving search engine quality.
摘要翻译：搜索相关性故障自动诊断。用户不满意的搜索结果可以通过各种机制报告他们的不满。不满意的报告可能引发自动调查，造成这种不满的根本原因。基于确定的根本原因，可以修改搜索引擎来解决创建不满意的问题，从而提高搜索引擎的质量。

5. 发明申请

US20110307479A1 Automatic Extraction of Structured Web Content 审中-公开
标题翻译：自动提取结构化Web内容
公开(公告)号：US20110307479A1
公开(公告)日：2011-12-15
申请号：US12797614
申请日：2010-06-10
申请人： Xiaoxin Yin , Wenzhao Tan , Xiao Li , Yi-Chin Tu , Yutaka Suzue , Johnson T. Apacible
发明人： Xiaoxin Yin , Wenzhao Tan , Xiao Li , Yi-Chin Tu , Yutaka Suzue , Johnson T. Apacible
IPC分类号： G06F17/30
CPC分类号： G06F16/9535
摘要： Described is extracting structured information from web pages for use in directly answering queries with data items from the structured data. Users' post-search browsing behaviors (search trails) are treated as implicit labels as to the relevance between web content and user queries, and are used to determine wrappers for extracting structured information. In one implementation, a system identifies websites from web search logs, builds wrappers from users' search trails, filters out bad wrappers (from inconsistent user clicks), and combines structured information from different web sites, e.g., for each query.
摘要翻译：描述的是从网页提取结构化信息，用于直接用来自结构化数据的数据项回答查询。用户的后搜索浏览行为（搜索路径）被视为Web内容和用户查询之间的相关性的隐含标签，并用于确定用于提取结构化信息的包装。在一个实现中，系统从网络搜索日志识别网站，从用户的搜索路径构建包装器，过滤掉不良包装器（来自不一致的用户点击），并且结合来自不同网站的结构化信息，例如针对每个查询。

6. 发明申请

US20120150838A1 AUTOMATED DATABASE GENERATION FOR ANSWERING FACT LOOKUP QUERIES 有权
标题翻译：自动数据库生成用于解答实际查询问题
公开(公告)号：US20120150838A1
公开(公告)日：2012-06-14
申请号：US12962677
申请日：2010-12-08
申请人： Xiaoxin Yin , Wenzhao Tan , Chao Liu
发明人： Xiaoxin Yin , Wenzhao Tan , Chao Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： Technologies pertaining to fact lookup queries are described herein. A relational database is automatically built by extracting attribute identities and attribute values from a one dimensional table, wherein the one dimensional table does not include an entity identity that corresponds to the attribute identity and the attribute value. The entity identity is inferred, and the attribute value is indexed in a relational database by the entity identity and the attribute identity. When a query is issued by a user that includes the entity identity and the attribute identity, the corresponding attribute value in the relational database is returned to the user.
摘要翻译：本文描述了与事实查找查询有关的技术。通过从一维表中提取属性标识和属性值来自动构建关系数据库，其中一维表不包括对应于属性标识和属性值的实体标识。推断出实体身份，并通过实体身份和属性身份在属性数据库中对属性值进行索引。当由包含实体标识和属性标识的用户发出查询时，将关系数据库中的对应属性值返回给用户。

7. 发明授权

US09460207B2 Automated database generation for answering fact lookup queries 有权
标题翻译：用于回答事实查询查询的自动数据库生成
公开(公告)号：US09460207B2
公开(公告)日：2016-10-04
申请号：US12962677
申请日：2010-12-08
申请人： Xiaoxin Yin , Wenzhao Tan , Chao Liu
发明人： Xiaoxin Yin , Wenzhao Tan , Chao Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： Technologies pertaining to fact lookup queries are described herein. A relational database is automatically built by extracting attribute identities and attribute values from a one dimensional table, wherein the one dimensional table does not include an entity identity that corresponds to the attribute identity and the attribute value. The entity identity is inferred, and the attribute value is indexed in a relational database by the entity identity and the attribute identity. When a query is issued by a user that includes the entity identity and the attribute identity, the corresponding attribute value in the relational database is returned to the user.
摘要翻译：本文描述了与事实查找查询有关的技术。通过从一维表中提取属性标识和属性值来自动构建关系数据库，其中一维表不包括对应于属性标识和属性值的实体标识。推断出实体身份，并通过实体身份和属性身份在属性数据库中对属性值进行索引。当由包含实体标识和属性标识的用户发出查询时，将关系数据库中的对应属性值返回给用户。

8. 发明申请

US20120278297A1 SEMI-SUPERVISED TRUTH DISCOVERY 审中-公开
标题翻译：半监督的真相发现
公开(公告)号：US20120278297A1
公开(公告)日：2012-11-01
申请号：US13097069
申请日：2011-04-29
申请人： Xiaoxin Yin , Wenzhao Tan
发明人： Xiaoxin Yin , Wenzhao Tan
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06N20/00
摘要： The described implementations relate to analysis of electronic data. One implementation provides a technique that can include accessing labeled and unlabeled assertions. The technique can also include identifying relationships between individual assertions. The technique can also include determining a confidence score for a first unlabeled assertion based on the relationships.
摘要翻译：所描述的实现涉及电子数据的分析。一个实现提供了一种技术，其可以包括访问带标签和未标记的断言。该技术还可以包括识别各个断言之间的关系。该技术还可以包括基于关系确定第一未标记断言的置信度分数。

9. 发明授权

US08145622B2 System for finding queries aiming at tail URLs 有权
标题翻译：用于查找针对尾部URL的查询的系统
公开(公告)号：US08145622B2
公开(公告)日：2012-03-27
申请号：US12351013
申请日：2009-01-09
申请人： Xiaoxin Yin , Vijay Ravindran Nair , Ryan Frederick Stewart , Fang Liu , Junhua Wang , Tiffany Kumi Dohzen , Yi-Min Wang
发明人： Xiaoxin Yin , Vijay Ravindran Nair , Ryan Frederick Stewart , Fang Liu , Junhua Wang , Tiffany Kumi Dohzen , Yi-Min Wang
IPC分类号： G06F7/00
CPC分类号： G06F17/30864
摘要： Systems and methodologies for improved query classification and processing are provided herein. As described herein, a query prediction model can be constructed from a set of training data (e.g., diagnostic data obtained from an automatic diagnostic system and/or other suitable data) using a machine learning-based technique. Subsequently upon receiving a query, a set of features corresponding to the query, such as the length and/or frequency of the query, unigram probabilities of respective words and/or groups of words in the query, presence of pre-designated words or phrases in the query, or the like, can be generated. The generated features can then be analyzed in combination with the query prediction model to classify the query by predicting whether the query is aimed at a head Uniform Resource Locator (URL) or a tail URL. Based on this prediction, an appropriate index or combination of indexes can be assigned to answer the query.
摘要翻译：本文提供了改进的查询分类和处理的系统和方法。如本文所述，可以使用基于机器学习的技术从一组训练数据（例如，从自动诊断系统获得的诊断数据和/或其他合适的数据）来构建查询预测模型。随后在接收到查询后，查询对应的一组特征，诸如查询的长度和/或频率，查询中各个单词和/或单词组的单位概率，预先指定的单词或短语的存在在查询等中可以生成。然后可以结合查询预测模型分析生成的特征，以通过预测查询是针对头统一资源定位符（URL）还是尾URL来对查询进行分类。基于该预测，可以分配适当的索引或索引组合来回答查询。

10. 发明申请

US20100179929A1 SYSTEM FOR FINDING QUERIES AIMING AT TAIL URLs 有权
标题翻译：在尾部URL中查找查询的系统
公开(公告)号：US20100179929A1
公开(公告)日：2010-07-15
申请号：US12351013
申请日：2009-01-09
申请人： Xiaoxin Yin , Vijay Ravindran Nair , Ryan Frederick Stewart , Fang Liu , Junhua Wang , Tiffany Kumi Dohzen , Yi-Min Wang
发明人： Xiaoxin Yin , Vijay Ravindran Nair , Ryan Frederick Stewart , Fang Liu , Junhua Wang , Tiffany Kumi Dohzen , Yi-Min Wang
IPC分类号： G06F15/18 , G06N5/02
CPC分类号： G06F17/30864
摘要： Systems and methodologies for improved query classification and processing are provided herein. As described herein, a query prediction model can be constructed from a set of training data (e.g., diagnostic data obtained from an automatic diagnostic system and/or other suitable data) using a machine learning-based technique. Subsequently upon receiving a query, a set of features corresponding to the query, such as the length and/or frequency of the query, unigram probabilities of respective words and/or groups of words in the query, presence of pre-designated words or phrases in the query, or the like, can be generated. The generated features can then be analyzed in combination with the query prediction model to classify the query by predicting whether the query is aimed at a head Uniform Resource Locator (URL) or a tail URL. Based on this prediction, an appropriate index or combination of indexes can be assigned to answer the query.
摘要翻译：本文提供了改进的查询分类和处理的系统和方法。如本文所述，可以使用基于机器学习的技术从一组训练数据（例如，从自动诊断系统获得的诊断数据和/或其他合适的数据）来构建查询预测模型。随后在接收到查询后，查询对应的一组特征，诸如查询的长度和/或频率，查询中各个单词和/或单词组的单位概率，预先指定的单词或短语的存在在查询等中可以生成。然后可以结合查询预测模型分析生成的特征，以通过预测查询是针对头统一资源定位符（URL）还是尾URL来对查询进行分类。基于该预测，可以分配适当的索引或索引组合来回答查询。

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