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1. 发明申请

US20070282699A1 Purchase Sequence Browser 有权
标题翻译：采购序列浏览器
公开(公告)号：US20070282699A1
公开(公告)日：2007-12-06
申请号：US11551683
申请日：2006-10-20
申请人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E. Rosario , Colin E. Little
发明人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E. Rosario , Colin E. Little
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0625 , G06Q30/0633 , G06Q30/0641 , G06Q30/0643 , G06Q40/04
摘要： The invention provides a purchase sequence browser (PuSB), i.e. a graphical user interface (GUI) that facilitates insight discovery and exploration of product affinities across time, generated by a purchase sequence analysis of a retailer's transaction data. A purchase sequence browser allows the user to browse the most significant product phrases discovered by an exhaustive search of the product affinities across time; explore the retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product; generate consistent purchase sequences given some constraints on the products and their order; and profile the value of a product across time with regard to other products fixed in time.
摘要翻译：本发明提供了购买序列浏览器（PuSB），即图形用户界面（GUI），其通过零售商的交易数据的购买序列分析产生的促进对时间的产品亲和力的洞察发现和探索。购买序列浏览器允许用户浏览通过对产品亲和力的详尽搜索发现的最重要的产品短语; 探索零售语法，从产品开始或结束时创建向前和向后的短语树或替代购买路径; 产生一致的采购顺序，给产品及其顺序带来一些限制; 并对与其他产品及时相关的产品的价值进行分析。

2. 发明授权

US07962368B2 Purchase sequence browser 有权
标题翻译：采购顺序浏览器
公开(公告)号：US07962368B2
公开(公告)日：2011-06-14
申请号：US11551683
申请日：2006-10-20
申请人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E Rosario , Colin E Little
发明人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E Rosario , Colin E Little
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0625 , G06Q30/0633 , G06Q30/0641 , G06Q30/0643 , G06Q40/04
摘要： The invention provides a purchase sequence browser (PuSB), i.e. a graphical user interface (GUI) that facilitates insight discovery and exploration of product affinities across time, generated by a purchase sequence analysis of a retailer's transaction data. A purchase sequence browser allows the user to browse the most significant product phrases discovered by an exhaustive search of the product affinities across time; explore the retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product; generate consistent purchase sequences given some constraints on the products and their order; and profile the value of a product across time with regard to other products fixed in time.
摘要翻译：本发明提供了购买序列浏览器（PuSB），即图形用户界面（GUI），其通过零售商的交易数据的购买序列分析产生的促进对时间的产品亲和力的洞察发现和探索。购买序列浏览器允许用户浏览通过对产品亲和力的详尽搜索发现的最重要的产品短语; 探索零售语法，从产品开始或结束时创建向前和向后的短语树或替代购买路径; 产生一致的采购顺序，给产品及其顺序带来一些限制; 并对与其他产品及时相关的产品的价值进行分析。

3. 发明授权

US08768743B2 Product space browser 有权
标题翻译：产品空间浏览器
公开(公告)号：US08768743B2
公开(公告)日：2014-07-01
申请号：US11625247
申请日：2007-01-19
申请人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Geraldine E Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
发明人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Geraldine E Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0603
摘要： A product space browser (PSB), which comprises a graphical user interface (GUI) that facilitates insight discovery through exploration and analysis of product space graphs generated by applying a product affinity engine to retailer's transaction data in a market basket context, is disclosed.
摘要翻译：公开了一种产品空间浏览器（PSB），其包括图形用户界面（GUI），其通过对通过在市场篮子上下文中对零售商的交易数据应用产品亲和度引擎而产生的产品空间图的探索和分析来促进洞察发现。

4. 发明申请

US20070118439A1 Product Space Browser 有权
标题翻译：产品空间浏览器
公开(公告)号：US20070118439A1
公开(公告)日：2007-05-24
申请号：US11625247
申请日：2007-01-19
申请人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
发明人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0603
摘要： A product space browser (PSB), which comprises a graphical user interface (GUI) that facilitates insight discovery through exploration and analysis of product space graphs generated by applying a product affinity engine to retailer's transaction data in a market basket context, is disclosed.
摘要翻译：公开了一种产品空间浏览器（PSB），其包括图形用户界面（GUI），其通过对通过在市场篮上下文中对零售商的交易数据应用产品亲和度引擎而产生的产品空间图的探索和分析来促进洞察发现。

5. 发明授权

US09633959B2 Integrated circuit die with corner IO pads 有权
公开(公告)号：US09633959B2
公开(公告)日：2017-04-25
申请号：US14620155
申请日：2015-02-11
申请人： Shailesh Kumar , Vikas Garg , Meng Kong Lye
发明人： Shailesh Kumar , Vikas Garg , Meng Kong Lye
IPC分类号： H01L23/48 , H01L23/52 , H01L23/00 , H01L23/31
CPC分类号： H01L24/06 , H01L23/3171 , H01L24/02 , H01L24/05 , H01L2224/0235 , H01L2224/02375 , H01L2224/04042 , H01L2224/05553 , H01L2224/05554 , H01L2224/05567 , H01L2224/0603 , H01L2224/06051 , H01L2224/06131 , H01L2224/06135 , H01L2224/06138 , H01L2224/06139 , H01L2224/06179 , H01L2924/00012
摘要： An integrated circuit (IC) die has side input/output (IO) pads located along each side of the die interior. Each die corner has a corner IO pad. The side IO pads adjacent to the corner IO pads have shortened passivation regions in the top metal layer (TML) that define TML access regions. TML traces run through the TML access regions to connect the corner IO pads to the die interior. Providing corner IO pads enables an IC die to have up to four more IO pads than a comparable conventional IC die that does not have any corner IO pads, or an IC die to have the same number of IO pads within a smaller overall footprint.

6. 发明授权

US08572618B2 Event driven change injection and dynamic extensions to a business process execution language process 有权
标题翻译：事件驱动的更改注入和业务流程执行语言流程的动态扩展
公开(公告)号：US08572618B2
公开(公告)日：2013-10-29
申请号：US12776064
申请日：2010-05-07
申请人： Khanderao Kand , Fang Liu , Bhagat Nainani , Shailesh Kumar
发明人： Khanderao Kand , Fang Liu , Bhagat Nainani , Shailesh Kumar
IPC分类号： G09F9/46
CPC分类号： G06F9/5038 , G06F2209/5013
摘要： An extensible process design provides an ability to dynamically inject changes into a running process instance, such as a BPEL instance. Using a combination of BPEL, rules and events, processes can be designed to allow flexibility in terms of adding new activities, removing or skipping activities and adding dependent activities. These changes do not require redeployment of the orchestration process and can affect the behavior of in-flight process instances. The extensible process design includes a main orchestration process, a set of task execution processes and a set of generic trigger processes. The design also includes a set of rules evaluated during execution of the tasks of the orchestration process. The design can further include three types of events: an initiate process event, a pre-task execution event and a post-task execution event. These events and rules can be used to alter the behavior of the main orchestration process at runtime.
摘要翻译：可扩展过程设计提供了将更改动态注入正在运行的流程实例（如BPEL实例）的功能。使用BPEL，规则和事件的组合，可以设计流程以允许在添加新活动，删除或跳过活动以及添加依赖活动方面的灵活性。这些更改不需要重新部署编排过程，并且可能影响飞行中流程实例的行为。可扩展过程设计包括主要的编排过程，一组任务执行过程和一组通用触发过程。该设计还包括在执行编排过程任务期间评估的一组规则。该设计可以进一步包括三种类型的事件：启动过程事件，前任务执行事件和后任务执行事件。这些事件和规则可用于在运行时改变主要业务流程的行为。

7. 发明授权

US08015140B2 Method and apparatus for recommendation engine using pair-wise co-occurrence consistency 有权
标题翻译：推荐引擎使用成对一致性的方法和装置
公开(公告)号：US08015140B2
公开(公告)日：2011-09-06
申请号：US12857317
申请日：2010-08-16
申请人： Shailesh Kumar , Edmond D. Chow , Michinari Momma
发明人： Shailesh Kumar , Edmond D. Chow , Michinari Momma
IPC分类号： G06F17/00 , G06N5/02
CPC分类号： G06Q30/06 , G06Q10/04 , G06Q10/06 , G06Q30/02 , G06Q30/0201 , G06Q30/0202 , G06Q30/0204 , G06Q30/0224 , G06Q30/0605
摘要： The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.
摘要翻译：本发明在本文中称为PeaCoCk，使用来自统计学，信息理论和图形理论的独特技术融合来量化和发现实体（例如产品和客户）之间的关系中的模式，如购买行为所证明的。与传统的基于购买频率的市场篮子分析技术（如大多数产生明显和虚假关联的关联规则）相反，PeaCoCk采用信息理论的一致性和相似性概念，这使得对真实的，统计上显着的和合乎逻辑的逻辑分析产品之间的关联。因此，PeaCoCk可以根据购买行为进行可靠，强大的预测分析。

8. 发明申请

US20100057509A1 CO-OCCURRENCE CONSISTENCY ANALYSIS METHOD AND APPARATUS FOR FINDING PREDICTIVE VARIABLE GROUPS 有权
标题翻译：共同一致性分析方法和发现预测变量组的装置
公开(公告)号：US20100057509A1
公开(公告)日：2010-03-04
申请号：US12202933
申请日：2008-09-02
申请人： Shailesh Kumar , Junwen Wu , Vesselin Diev
发明人： Shailesh Kumar , Junwen Wu , Vesselin Diev
IPC分类号： G06Q10/00
CPC分类号： G06Q10/10
摘要： A method of modeling includes quantifying a co-operative strength value for a plurality of pairs of variables, and identifying a clique of at least three variables based on a graph of the co-operative strength values of a plurality of pairs of variables. The method also includes selecting a first pair of variables of the plurality of pairs of variables having a high co-operative strength value. A second clique may also be identified. A model of the first clique and a model of the second clique are made. The outputs of these models are combined to form a combined model which is used to make various decisions with respect to real time data.
摘要翻译：建模方法包括量化多对变量对的合作强度值，并且基于多对变量对的合作强度值的图来识别至少三个变量的集团。该方法还包括选择具有高合作强度值的多对变量对的第一对变量。也可以识别第二集团。制作第一集团的模型和第二集团的模型。这些模型的输出被组合以形成用于对实时数据做出各种决定的组合模型。

9. 发明申请

US20090327132A1 INCREMENTAL FACTORIZATION-BASED SMOOTHING OF SPARSE MULTI-DIMENSIONAL RISK TABLES 有权
标题翻译：稀疏多维风险表的基于加速制造的平滑
公开(公告)号：US20090327132A1
公开(公告)日：2009-12-31
申请号：US12163688
申请日：2008-06-27
申请人： Vesselin Diev , Shailesh Kumar , Scott M. Zoldi
发明人： Vesselin Diev , Shailesh Kumar , Scott M. Zoldi
IPC分类号： G06Q40/00
CPC分类号： G06Q40/02 , G06Q20/40 , G06Q40/00 , G06Q40/025
摘要： A system for classifying a transaction as fraudulent includes a training component and a scoring component. The training component acts on historical data and also includes a multi-dimensional risk table component comprising one or more multidimensional risk tables each of which approximates an initial risk value for a substantially empty cell in a risk table based upon risk values in cells related to the substantially empty cell. The scoring component produces a score, based in part, on the risk tables associated with groupings of variables having values determined by the training component. The scoring component includes a statistical model that produces an output and wherein the transaction is classified as fraudulent when the output is above a selected threshold value.
摘要翻译：将交易分类为欺诈的系统包括训练组件和评分组件。培训组件作用于历史数据，并且还包括多维风险表组件，其包括一个或多个多维风险表，每个风险表基于与风险表相关的单元中的风险值近似于风险表中基本上为空的单元格的初始风险值基本上空的单元格。评分部分产生一个分数，部分基于与具有由训练组件确定的值的变量分组相关联的风险表。评分组件包括产生输出的统计模型，并且其中当输出高于所选择的阈值时，交易被分类为欺诈。

10. 发明申请

US20070094067A1 Method and apparatus for recommendation engine using pair-wise co-occurrence consistency 有权
公开(公告)号：US20070094067A1
公开(公告)日：2007-04-26
申请号：US11355567
申请日：2006-02-15
申请人： Shailesh Kumar , Edmond Chow , Michinari Momma
发明人： Shailesh Kumar , Edmond Chow , Michinari Momma
IPC分类号： G06F17/30
CPC分类号： G06Q30/06 , G06Q10/04 , G06Q10/06 , G06Q30/02 , G06Q30/0201 , G06Q30/0202 , G06Q30/0204 , G06Q30/0224 , G06Q30/0605
摘要： The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.

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