公开(公告)号：US20130046768A1

公开(公告)日：2013-02-21

申请号：US13213856

申请日：2011-08-19

申请人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

发明人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

IPC分类号： G06F17/30

CPC分类号： G06F17/3053 ,  G06F17/30592 ,  G06F17/30958 ,  G06F2216/03

摘要： A method, system and computer program product for finding a diversified ranking list for a given query. In one embodiment, a multitude of date items responsive to the query are identified, a marginal score is established for each data item; and a set, or ranking list, of the data items is formed based on these scores. This ranking list is formed by forming an initial set, and one or more data items are added to the ranking list based on the marginal scores of the data items. In one embodiment, each of the data items has a measured relevance and a measured diversity value, and the marginal scores for the data items are based on the measured relevance and the measured diversity values of the data items.

摘要翻译： 一种用于查找给定查询的多样化排名列表的方法，系统和计算机程序产品。 在一个实施例中，识别响应于查询的多个日期项目，为每个数据项目建立边际分数; 并且基于这些分数形成数据项的集合或排名列表。 该排序列表通过形成初始集合而形成，并且基于数据项目的边际分数将一个或多个数据项目添加到排名列表。 在一个实施例中，每个数据项具有测量的相关性和测量的分集值，并且数据项的边际分数基于所测量的相关性和所测量的数据项的分集值。

公开(公告)号：US09009147B2

公开(公告)日：2015-04-14

申请号：US13213856

申请日：2011-08-19

申请人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

发明人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

IPC分类号： G06F17/30 ,  G06F7/00

CPC分类号： G06F17/3053 ,  G06F17/30592 ,  G06F17/30958 ,  G06F2216/03

摘要： A method, system and computer program product for finding a diversified ranking list for a given query. In one embodiment, a multitude of date items responsive to the query are identified, a marginal score is established for each data item; and a set, or ranking list, of the data items is formed based on these scores. This ranking list is formed by forming an initial set, and one or more data items are added to the ranking list based on the marginal scores of the data items. In one embodiment, each of the data items has a measured relevance and a measured diversity value, and the marginal scores for the data items are based on the measured relevance and the measured diversity values of the data items.

摘要翻译： 一种用于查找给定查询的多样化排名列表的方法，系统和计算机程序产品。 在一个实施例中，识别响应于查询的多个日期项目，为每个数据项目建立边际分数; 并且基于这些分数形成数据项的集合或排名列表。 该排序列表通过形成初始集合而形成，并且基于数据项目的边际分数将一个或多个数据项目添加到排名列表。 在一个实施例中，每个数据项具有测量的相关性和测量的分集值，并且数据项的边际分数基于所测量的相关性和所测量的数据项的分集值。

公开(公告)号：US20130339919A1

公开(公告)日：2013-12-19

申请号：US13526152

申请日：2012-06-18

申请人： Robert J. Baseman ,  Jingrui He ,  Yada Zhu

发明人： Robert J. Baseman ,  Jingrui He ,  Yada Zhu

IPC分类号： G06F17/50

CPC分类号： G06Q10/04 ,  G05B19/41875 ,  Y02P90/22 ,  Y02P90/26

摘要： A method for performing enhanced wafer quality prediction in a semiconductor manufacturing process includes the steps of: obtaining data including at least one of tensor format wafer processing conditions, historical wafer quality measurements and prior knowledge relating to at least one of the semiconductor manufacturing process and wafer quality; building a hierarchical prediction model including at least the tensor format wafer processing conditions; and predicting wafer quality for a newly fabricated wafer based at least on the hierarchical prediction model and corresponding tensor format wafer processing conditions.

摘要翻译： 一种用于在半导体制造过程中执行增强的晶片质量预测的方法包括以下步骤：获得包括张量格式晶片处理条件，历史晶片质量测量和与半导体制造工艺和晶片中的至少一个相关的先前知识中的至少一个的数据 质量; 构建包括至少张量格式晶片处理条件的分级预测模型; 并且至少基于分层预测模型和对应的张量格式晶片处理条件来预测新制造的晶片的晶片质量。

公开(公告)号：US20130338808A1

公开(公告)日：2013-12-19

申请号：US13559500

申请日：2012-07-26

申请人： Robert J. Baseman ,  Jingrui He ,  Yada Zhu

发明人： Robert J. Baseman ,  Jingrui He ,  Yada Zhu

IPC分类号： G06F19/00

CPC分类号： G06Q10/04 ,  G05B19/41875 ,  Y02P90/22 ,  Y02P90/26

摘要： An apparatus for performing enhanced wafer quality prediction in a semiconductor manufacturing process includes memory, for storing historical data relating to the semiconductor manufacturing process, and at least one processor in operative communication with the memory. The processor is operative: to obtain data including tensor format wafer processing conditions, historical wafer quality measurements and/or prior knowledge relating to at least one of the semiconductor manufacturing process and wafer quality; to build a hierarchical prediction model including at least the tensor format wafer processing conditions; and to predict wafer quality for a newly fabricated wafer based at least on the hierarchical prediction model and corresponding tensor format wafer processing conditions.

摘要翻译： 用于在半导体制造工艺中执行增强的晶片质量预测的装置包括用于存储与半导体制造过程有关的历史数据的存储器以及与存储器可操作地通信的至少一个处理器。 处理器可操作：获得包括张量格式晶片处理条件，历史晶片质量测量和/或与半导体制造工艺和晶片质量中的至少一个相关的先前知识的数据; 构建至少包括张量格式晶片处理条件的分层预测模型; 并且至少基于分级预测模型和对应的张量格式晶片处理条件来预测新制造的晶片的晶片质量。

公开(公告)号：US20130046769A1

公开(公告)日：2013-02-21

申请号：US13213872

申请日：2011-08-19

申请人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

发明人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

IPC分类号： G06F17/30

CPC分类号： G06F16/24578 ,  G06F16/334 ,  G06F16/9024

摘要： A method, system and computer program product for measuring a relevance and diversity of a ranking list to a given query. The ranking list is comprised of a set of data items responsive to the query. In one embodiment, the method comprises calculating a measured relevance of the set of data items to the query using a defined relevance measuring procedure, and determining a measured diversity value for the ranking list using a defined diversity measuring procedure. The measured relevance and the measured diversity value are combined to obtain a measure of the combined relevance and diversity of the ranking list. The measured relevance of the set of data items may be based on the individual relevance of each of the data items to the query, and the diversity value may be based on the similarities of the data items to each other.

摘要翻译： 一种用于测量给定查询的排名列表的相关性和多样性的方法，系统和计算机程序产品。 排名表由一组响应于查询的数据项组成。 在一个实施例中，所述方法包括使用定义的相关度测量程序来计算所述数据项集合对所述查询的测量相关性，以及使用定义的分集测量过程来确定所述排名列表的测量分集值。 将测量的相关性和测量的多样性值组合以获得排名列表的组合相关性和多样性的度量。 所述数据集合的所测量的相关性可以基于每个数据项到查询的个体相关性，并且分集值可以基于数据项彼此的相似度。