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1. 发明申请

US20090006392A1 DATA PROFILE COMPUTATION 有权
标题翻译：数据配置文件计算
公开(公告)号：US20090006392A1
公开(公告)日：2009-01-01
申请号：US11769050
申请日：2007-06-27
申请人： Zhimin Chen , Venkatesh Ganti , Gunjan Jha , Shriraghav Kaushik , Vivek Narasayya
发明人： Zhimin Chen , Venkatesh Ganti , Gunjan Jha , Shriraghav Kaushik , Vivek Narasayya
IPC分类号： G06F7/06 , G06F17/30
CPC分类号： G06F17/30536
摘要： Architecture that provides a data profile computation technique which employs key profile computation and data pattern profile computation. Key profile computation in a data table includes both exact keys as well as approximate keys, and is based on key strengths. A key strength of 100% is an exact key, and any other percentage in an approximate key. The key strength is estimated based on the number of table rows that have duplicated attribute values. Only column sets that exceed a threshold value are returned. Pattern profiling identifies a small set of regular expression patterns which best describe the patterns within a given set of attribute values. Pattern profiling includes three phases: a first phases for determining token regular expressions, a second phase for determining candidate regular expressions, and a third phase for identifying the best regular expressions of the candidates that match the attribute values.
摘要翻译：提供采用关键轮廓计算和数据模式轮廓计算的数据轮廓计算技术的架构。数据表中的关键轮廓计算包括精密键和近似键，并且基于关键优点。 100％的关键优势是一个确切的关键，其中一个关键的任何其他百分比。基于具有重复的属性值的表行的数量来估计关键强度。只返回超过阈值的列集。模式分析标识一组最佳描述一组给定属性值中的模式的正则表达式模式。模式分析包括三个阶段：用于确定令牌正则表达式的第一阶段，用于确定候选正则表达式的第二阶段，以及用于识别与属性值匹配的候选的最佳正则表达式的第三阶段。

2. 发明申请

US20060253422A1 Efficient computation of multiple group by queries 审中-公开
标题翻译：通过查询高效计算多组
公开(公告)号：US20060253422A1
公开(公告)日：2006-11-09
申请号：US11124516
申请日：2005-05-06
申请人： Vivek Narasayya , Zhimin Chen
发明人： Vivek Narasayya , Zhimin Chen
IPC分类号： G06F17/30
CPC分类号： G06F16/24535
摘要： Systems and methodologies for computation of multiple group by queries via an optimizer that examines the space of plans in a systematic and cost based manner. The optimizer includes a merging component to merge pairs of sub plans to facilitate a plan choice with a lowest cost. The merging component can take as input two sub plans (e.g., sub plan P1 with root node V1 and sub plan P2 with root node V2, wherein each sub plan is a sub-tree of a logical plan whose root node is directly pointed to a Relation “R”), to return a set of sub-plans as out put with a root node V1∪V2 that is the smallest relation from which both V1 and V2 can be computed.
摘要翻译：用于通过查询计算多组的系统和方法，该优化器以系统和成本为基础的方式检查计划的空间。优化器包括合并组件以合并子计划对，以便以最低成本进行计划选择。合并组件可以将根节点V <1>和子计划P <2> 的子计划（例如，子计划P＆lt; 1＆lt; 1＆gt; 节点V 2，其中每个子计划是逻辑计划的子树，其根节点直接指向关系“R”），以返回一组子计划，如与作为V SUB 1和V 2 2两者之间的最小关系的根节点V 1 2 V 2 2＆lt; 1＆lt; 1＆lt; 计算。

3. 发明申请

US20120323921A1 DICTIONARY FOR HIERARCHICAL ATTRIBUTES FROM CATALOG ITEMS 有权
标题翻译：来自目录项目的分类属性的词典
公开(公告)号：US20120323921A1
公开(公告)日：2012-12-20
申请号：US13160532
申请日：2011-06-15
申请人： Zhimin Chen , Eduardo Laureano , Renfei Luo , Tsheko Mutungu , Vivek Narasayya , David Talby
发明人： Zhimin Chen , Eduardo Laureano , Renfei Luo , Tsheko Mutungu , Vivek Narasayya , David Talby
IPC分类号： G06F17/30
CPC分类号： G06F17/30616
摘要： A plurality of items included in a catalog may be obtained, each item associated with an item category. Brand indicators may be obtained, each brand indicator associated with the item category. Brand indicators associated with each of the items may be determined, and the each item may be assigned to a partition group associated with the brand indicator that is associated with the each item. Correlated string tokens that are correlated, greater than a predetermined correlation threshold value, with the brand indicator associated with the partition group that is associated with the each one of the items, the correlated string tokens associated with the each one of the plurality of items, may be determined. A dictionary hierarchy may be generated based on the one or more correlated string tokens.
摘要翻译：可以获得包括在目录中的多个项目，每个项目与项目类别相关联。可以获得品牌指标，每个品牌指标与项目类别相关联。可以确定与每个项目相关联的品牌指示符，并且可以将每个项目分配给与与每个项目相关联的品牌指示符相关联的分区组。与相关联的字符串令牌，大于预定的相关阈值，与与与每个项目相关联的分区组相关联的品牌指示符，与多个项目中的每一个相关联的相关联的字符串令牌，可以确定。可以基于一个或多个相关串令牌来生成词典层次。

4. 发明授权

US07720883B2 Key profile computation and data pattern profile computation 有权
标题翻译：关键轮廓计算和数据模式轮廓计算
公开(公告)号：US07720883B2
公开(公告)日：2010-05-18
申请号：US11769050
申请日：2007-06-27
申请人： Zhimin Chen , Venkatesh Ganti , Gunjan Jha , Shriraghav Kaushik , Vivek Narasayya
发明人： Zhimin Chen , Venkatesh Ganti , Gunjan Jha , Shriraghav Kaushik , Vivek Narasayya
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30536
摘要： Architecture that provides a data profile computation technique which employs key profile computation and data pattern profile computation. Key profile computation in a data table includes both exact keys as well as approximate keys, and is based on key strengths. A key strength of 100% is an exact key, and any other percentage in an approximate key. The key strength is estimated based on the number of table rows that have duplicated attribute values. Only column sets that exceed a threshold value are returned. Pattern profiling identifies a small set of regular expression patterns which best describe the patterns within a given set of attribute values. Pattern profiling includes three phases: a first phases for determining token regular expressions, a second phase for determining candidate regular expressions, and a third phase for identifying the best regular expressions of the candidates that match the attribute values.
摘要翻译：提供采用关键轮廓计算和数据模式轮廓计算的数据轮廓计算技术的架构。数据表中的关键轮廓计算包括精密键和近似键，并且基于关键优点。 100％的关键优势是一个确切的关键，其中一个关键的任何其他百分比。基于具有重复的属性值的表行的数量来估计关键强度。只返回超过阈值的列集。模式分析标识一组最佳描述一组给定属性值中的模式的正则表达式模式。模式分析包括三个阶段：用于确定令牌正则表达式的第一阶段，用于确定候选正则表达式的第二阶段，以及用于识别与属性值匹配的候选的最佳正则表达式的第三阶段。

5. 发明授权

US09547718B2 High precision set expansion for large concepts 有权
标题翻译：高精度集扩展为大概念
公开(公告)号：US09547718B2
公开(公告)日：2017-01-17
申请号：US13325072
申请日：2011-12-14
申请人： Jiewen Huang , Zhimin Chen , Arvind Arasu , Vivek Narasayya
发明人： Jiewen Huang , Zhimin Chen , Arvind Arasu , Vivek Narasayya
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06Q30/0201
摘要： A set expansion system is described herein that improves precision, recall, and performance of prior set expansion methods for large sets of data. The system maintains high precision and recall by 1) identifying the qualify of particular lists and applying that quality through a weight, 2) allowing for the specification or negative examples in a set of seeds to reduce the introduction of bad entities into the set, and 3) applying a cutoff to eliminate lists that include a low number of positive matches. The system may perform multiple passes to first generate a good candidate result set and then refine the set to find a set with highest quality. The system may also apply Map Reduce or other distributed processing techniques to allow calculation in parallel. Thus, the system efficiently expands large concept sets from a potentially small set of initial seeds from readily available web data.
摘要翻译：本文描述了一种扩展系统，可提高大型数据集的先前设置扩展方法的精度，调用和性能。该系统通过1）确定特定列表的资格并通过权重来应用该质量，保持高精度和召回; 2）允许一组种子中的规范或否定示例，以减少将不良实体引入到集合中; 3）应用截止值来消除包括少量正匹配的列表。系统可以执行多次通过以首先产生良好的候选结果集合，然后对该集合进行优化以找到具有最高质量的集合。该系统还可以应用Map Reduce或其他分布式处理技术来并行计算。因此，系统从容易获得的网络数据的一小部分初始种子中有效地扩展了大概念集。

6. 发明授权

US08606788B2 Dictionary for hierarchical attributes from catalog items 有权
标题翻译：目录项目的层次属性字典
公开(公告)号：US08606788B2
公开(公告)日：2013-12-10
申请号：US13160532
申请日：2011-06-15
申请人： Zhimin Chen , Eduardo Laureano , Renfei Luo , Tsheko Mutungu , Vivek Narasayya , David Talby
发明人： Zhimin Chen , Eduardo Laureano , Renfei Luo , Tsheko Mutungu , Vivek Narasayya , David Talby
IPC分类号： G06F17/30
CPC分类号： G06F17/30616
摘要： A plurality of items included in a catalog may be obtained, each item associated with an item category. Brand indicators may be obtained, each brand indicator associated with the item category. Brand indicators associated with each of the items may be determined, and the each item may be assigned to a partition group associated with the brand indicator that is associated with the each item. Correlated string tokens that are correlated, greater than a predetermined correlation threshold value, with the brand indicator associated with the partition group that is associated with the each one of the items, the correlated string tokens associated with the each one of the plurality of items, may be determined. A dictionary hierarchy may be generated based on the one or more correlated string tokens.
摘要翻译：可以获得包括在目录中的多个项目，每个项目与项目类别相关联。可以获得品牌指标，每个品牌指标与项目类别相关联。可以确定与每个项目相关联的品牌指示符，并且可以将每个项目分配给与与每个项目相关联的品牌指示符相关联的分区组。与相关联的字符串令牌，大于预定的相关阈值，与与与每个项目相关联的分区组相关联的品牌指示符，与多个项目中的每一个相关联的相关联的字符串令牌，可以确定。可以基于一个或多个相关串令牌来生成词典层次。

7. 发明申请

US20130159317A1 HIGH PRECISION SET EXPANSION FOR LARGE CONCEPTS 有权
标题翻译：高精度扩展大概念
公开(公告)号：US20130159317A1
公开(公告)日：2013-06-20
申请号：US13325072
申请日：2011-12-14
申请人： Jiewen Huang , Zhimin Chen , Arvind Arasu , Vivek Narasayya
发明人： Jiewen Huang , Zhimin Chen , Arvind Arasu , Vivek Narasayya
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06Q30/0201
摘要： A set expansion system is described herein that improves precision, recall, and performance of prior set expansion methods for large sets of data. The system maintains high precision and recall by 1) identifying the qualify of particular lists and applying that quality through a weight, 2) allowing for the specification or negative examples in a set of seeds to reduce the introduction of bad entities into the set, and 3) applying a cutoff to eliminate lists that include a low number of positive matches. The system may perform multiple passes to first generate a good candidate result set and then refine the set to find a set with highest quality. The system may also apply Map Reduce or other distributed processing techniques to allow calculation in parallel. Thus, the system efficiently expands large concept sets from a potentially small set of initial seeds from readily available web data.
摘要翻译：本文描述了一种扩展系统，可提高大型数据集的先前设置扩展方法的精度，调用和性能。该系统通过1）确定特定列表的资格并通过权重来应用该质量，保持高精度和召回; 2）允许一组种子中的规范或否定示例，以减少将不良实体引入到集合中; 3）应用截止值来消除包括少量正匹配的列表。系统可以执行多次通过以首先产生良好的候选结果集合，然后对该集合进行优化以找到具有最高质量的集合。该系统还可以应用Map Reduce或其他分布式处理技术来并行计算。因此，系统从容易获得的网络数据的一小部分初始种子中有效地扩展了大概念集。

8. 外观设计

USD938638S1 Solar light 有权
公开(公告)号：USD938638S1
公开(公告)日：2021-12-14
申请号：US29728175
申请日：2020-03-17
申请人： Zhimin Chen
设计人： Zhimin Chen

9. 发明申请

US20130346464A1 Data Services for Enterprises Leveraging Search System Data Assets 审中-公开
标题翻译：企业数据服务利用搜索系统数据资产
公开(公告)号：US20130346464A1
公开(公告)日：2013-12-26
申请号：US13527601
申请日：2012-06-20
申请人： Tao Cheng , Kris Ganjam , Kaushik Chakrabarti , Zhimin Chen , Vivek R. Narasayya , Surajit Chaudhuri
发明人： Tao Cheng , Kris Ganjam , Kaushik Chakrabarti , Zhimin Chen , Vivek R. Narasayya , Surajit Chaudhuri
IPC分类号： G06F15/16
CPC分类号： G06Q10/10
摘要： A data service system is described herein which processes raw data assets from at least one network-accessible system (such as a search system), to produce processed data assets. Enterprise applications can then leverage the processed data assets to perform various environment-specific tasks. In one implementation, the data service system can generate any of: synonym resources for use by an enterprise application in providing synonyms for specified terms associated with entities; augmentation resources for use by an enterprise application in providing supplemental information for specified seed information; and spelling-correction resources for use by an enterprise application in providing spelling information for specified terms, and so on.
摘要翻译：本文描述了一种数据服务系统，其处理来自至少一个网络可访问系统（例如搜索系统）的原始数据资产以产生处理的数据资产。企业应用程序可以利用已处理的数据资产来执行各种环境特定任务。在一个实现中，数据服务系统可以生成以下任何一种：供企业应用使用的同义词资源，为与实体相关联的指定术语提供同义词; 增加资源供企业应用用于提供指定种子信息的补充信息; 以及企业应用程序为指定的术语提供拼写信息的拼写纠正资源等。

10. 发明申请

US20110264598A1 PRODUCT SYNTHESIS FROM MULTIPLE SOURCES 有权
标题翻译：多源产品合成
公开(公告)号：US20110264598A1
公开(公告)日：2011-10-27
申请号：US12764676
申请日：2010-04-21
申请人： Ariel Fuxman , Hoa Nguyen , Juliana Freire de Lima e Silva , Stelios Paparizos , Rakesh Agrawal , Zhimin Chen , Lawrence William Colagiovanni , Prakash Sikchi
发明人： Ariel Fuxman , Hoa Nguyen , Juliana Freire de Lima e Silva , Stelios Paparizos , Rakesh Agrawal , Zhimin Chen , Lawrence William Colagiovanni , Prakash Sikchi
IPC分类号： G06Q10/00 , G06Q30/00
CPC分类号： G06F17/30386 , G06Q30/0281 , G06Q30/0603
摘要： Methods and systems for automatically synthesizing product information from multiple data sources into an on-line catalog are disclosed, and in particular, for automatically synthesizing the product information based on attribute-value pairs. Information for a product may be obtained, via entity extraction, feed ingestion, and other mechanisms, from a plurality of structured and unstructured data sources having different taxonomies and schemas. Product information may additionally or alternatively be obtained or derived based on popularity data. The product information may be cleansed, segmented and normalized. The product information may be clustered so closest products, attribute names and attribute values are associated. A representative value for an attribute name may be determined, and the on-line catalog may be updated so that entries are comprehensive, meaningful and useful to a catalog user. Updates from at least 500 million different data sources may be scheduled to occur as frequently as several times daily.
摘要翻译：公开了用于将产品信息从多个数据源自动合成到在线目录中的方法和系统，特别地，用于基于属性值对自动合成产品信息。可以通过实体提取，饲料摄取和其他机制从具有不同分类和模式的多个结构化和非结构化数据源获得信息。产品信息可以另外地或替代地基于流行度数据获得或导出。产品信息可以被清洁，分段和归一化。产品信息可能被聚集，因此最接近的产品，属性名称和属性值相关联。可以确定属性名称的代表值，并且可以更新在线目录，使得条目对目录用户是全面的，有意义的和有用的。可能会安排从至少5亿个不同数据源进行更新，频繁发生，每天多次。

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