公开(公告)号：US08738489B2

公开(公告)日：2014-05-27

申请号：US12912953

申请日：2010-10-27

Applicant: John Clark, Jr. ,  Shailesh Kumar ,  Fang Liu ,  David Battaglia

Inventor： John Clark, Jr. ,  Shailesh Kumar ,  Fang Liu ,  David Battaglia

IPC: G06Q40/00 ,  G06Q40/02

CPC classification number: G06Q40/02 ,  G06Q40/00

Abstract: A computer-readable medium, computer-implemented method, and financial close management system are provided that manage a schedule. A schedule is a core object of the financial close management system, and is an expression of a template. Managing a schedule can include creating a new schedule, modifying an existing schedule, deleting an existing schedule, duplicating an existing schedule, validating an existing schedule, creating a template from an existing schedule, setting a status of an existing schedule, and importing and exporting an existing schedule. In addition, managing a schedule can include defining task type parameters that can be set during scheduling and setting task parameters of a schedule at a schedule level rather than a task level.

Abstract translation: 提供了一种管理时间表的计算机可读介质，计算机实现的方法和财务关闭管理系统。 计划是财务关闭管理系统的核心对象，是模板的表达。 管理时间表可以包括创建新的时间表，修改现有时间表，删除现有时间表，复制现有时间表，验证现有时间表，从现有时间表创建模板，设置现有时间表的状态，以及导入和导出 现有时间表。 此外，管理时间表可以包括定义可以在调度期间设置的任务类型参数，并且在调度级别而不是任务级别设置调度的任务参数。

公开(公告)号：US08725747B2

公开(公告)日：2014-05-13

申请号：US12912969

申请日：2010-10-27

Applicant: John Clark, Jr. ,  Shailesh Kumar ,  Chuck Spencer ,  Peter Toukhanian

Inventor： John Clark, Jr. ,  Shailesh Kumar ,  Chuck Spencer ,  Peter Toukhanian

IPC: G06F17/30

CPC classification number: G06F17/30554 ,  G06Q10/06

Abstract: A computer-readable medium, computer-implemented method, and system are provided for filtering of custom attributes. A custom attribute is an attribute of an object defined by a user. Once a user has defined one or more custom attributes, the user can filter a set of objects based on a criteria that includes a value for one or more custom attributes. The filtering can be dynamic so that when the set of objects is modified (such as creating a new object, deleting an existing object, or modifying an existing object), the filter is automatically updated. Furthermore, a filtering criteria can be based on the set of objects present in the system, so that any filter that is defined returns at least one object. In addition, once a filter is applied, any additional filter applied to the original filter can have a filtering criteria based on the subset of objects returned by the original filter.

Abstract translation: 提供计算机可读介质，计算机实现的方法和系统来过滤自定义属性。 自定义属性是用户定义的对象的属性。 一旦用户定义了一个或多个自定义属性，用户可以基于包含一个或多个自定义属性的值的条件过滤一组对象。 过滤可以是动态的，以便当对象集合进行修改（例如创建新对象，删除现有对象或修改现有对象）时，过滤器将自动更新。 此外，过滤标准可以基于系统中存在的对象集合，使得定义的任何过滤器返回至少一个对象。 此外，一旦应用过滤器，应用于原始过滤器的任何附加过滤器可以具有基于原始过滤器返回的对象子集的过滤标准。

公开(公告)号：US08417559B2

公开(公告)日：2013-04-09

申请号：US12110171

申请日：2008-04-25

Applicant: Ashutosh Umakant Joshi ,  Zhenyu Yan ,  Marc-david Cohen ,  Shailesh Kumar

Inventor： Ashutosh Umakant Joshi ,  Zhenyu Yan ,  Marc-david Cohen ,  Shailesh Kumar

IPC: G06Q30/00

CPC classification number: G06Q30/02 ,  G06Q30/0202

Abstract: A computer-implemented method described for facilitating selection of an assortment of products to offer for sale. The method includes receiving transaction data representing characteristics of a plurality of commercial transactions including a first product and a second product. Product attribute data representing attributes for at least the two products are also received. Substitution demand data for the second product is estimated which represents demand for the second product given the first product is not available, the estimation being based on the transaction data and product attribute data.

Abstract translation: 描述了一种计算机实现的方法，用于促进选择提供出售的各种产品。 该方法包括接收表示包括第一产品和第二产品的多个商业交易的特征的交易数据。 还收到表示至少两个产品的属性的产品属性数据。 估计第二产品的替代需求数据，其代表第一产品不可用的第二产品的需求，该估计基于交易数据和产品属性数据。

公开(公告)号：US08355896B2

公开(公告)日：2013-01-15

申请号：US12202933

申请日：2008-09-02

Applicant: Shailesh Kumar ,  Junwen Wu ,  Vesselin Diev

Inventor： Shailesh Kumar ,  Junwen Wu ,  Vesselin Diev

IPC: G06F17/50 ,  G06Q30/00 ,  G06Q99/00

CPC classification number: G06Q10/10

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20120310930A1

公开(公告)日：2012-12-06

申请号：US13219846

申请日：2011-08-29

Applicant: Shailesh Kumar ,  Mahesh Chhaparia

Inventor： Shailesh Kumar ,  Mahesh Chhaparia

IPC: G06F17/30

CPC classification number: G06F17/30648 ,  G06F17/30719

Abstract: Given a set of documents relevant to a litigation hold and a seed set of keywords, a second set of keywords can be generated and suggested to a user. Each document in a training set of documents is given an indication of relevance. Based on the indication of relevance, a set of further keywords relevant to the litigation is extracted from the documents and suggested to a user. The suggested set of keywords may or may not include keywords in the seed set. Additionally, the suggested set of keywords may be related to the seed set of keywords.

Abstract translation: 给定与诉讼保留相关的一组文档和一组关键字，可以为用户生成并建议第二组关键字。 培训文件中的每个文件都有相关性的指示。 根据相关性的指示，从文件中提取与诉讼相关的一组进一步的关键词，并向用户提出建议。 建议的一组关键字可能包含或不包括种子集中的关键字。 此外，建议的一组关键字可能与关键字的种子集有关。

公开(公告)号：US08049817B2

公开(公告)日：2011-11-01

申请号：US12286798

申请日：2008-10-02

Applicant: Shekhar Madnani ,  Shailesh Kumar

Inventor： Shekhar Madnani ,  Shailesh Kumar

IPC: H04N7/01

CPC classification number: H04N17/00 ,  H04N5/142 ,  H04N5/145

Abstract: A method and system for calculating an interlace artifact in image data are disclosed. A motion picture of the image data comprises a series of frames, captured at a predefined interval of time. During processing of the motion picture, the frames are divided into fields, each field comprising one or more pixels. A difference between the pixels of the fields is calculated. Thereafter, edges of the pixels are calculated in the fields. The method and system then identify the focused area in the fields. To calculate the interlace artifact in the motion picture, the displacement of the focused area is calculated by using motion vectors. The artifacts are calculated as a ratio of a number of pixels based on motion vector calculation.

Abstract translation: 公开了一种用于计算图像数据中的隔行伪影的方法和系统。 图像数据的运动图像包括以预定的时间间隔捕获的一系列帧。 在运动图像的处理期间，帧被分成场，每个场包括一个或多个像素。 计算场的像素之间的差异。 此后，在场中计算像素的边缘。 然后，该方法和系统确定了该领域的重点领域。 为了计算运动图像中的交错伪影，通过使用运动矢量来计算聚焦区域的位移。 伪像被计算为基于运动矢量计算的像素数的比率。

公开(公告)号：US07962368B2

公开(公告)日：2011-06-14

申请号：US11551683

申请日：2006-10-20

Applicant: Shailesh Kumar ,  Megan Thorsen ,  Ashutosh Joshi ,  Sergei Tolmanov ,  Helen Geraldine E Rosario ,  Colin E Little

Inventor： Shailesh Kumar ,  Megan Thorsen ,  Ashutosh Joshi ,  Sergei Tolmanov ,  Helen Geraldine E Rosario ,  Colin E Little

IPC: G06Q30/00

CPC classification number: G06Q30/02 ,  G06Q30/0601 ,  G06Q30/0625 ,  G06Q30/0633 ,  G06Q30/0641 ,  G06Q30/0643 ,  G06Q40/04

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US07685021B2

公开(公告)日：2010-03-23

申请号：US11355567

申请日：2006-02-15

Applicant: Shailesh Kumar ,  Edmond D. Chow ,  Michinari Momma

Inventor： Shailesh Kumar ,  Edmond D. Chow ,  Michinari Momma

IPC: G06Q30/00

CPC classification number: G06Q30/06 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0204 ,  G06Q30/0224 ,  G06Q30/0605

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US07672865B2

公开(公告)日：2010-03-02

申请号：US11256386

申请日：2005-10-21

Applicant: Shailesh Kumar ,  Edmond D. Chow ,  Michinari Momma

Inventor： Shailesh Kumar ,  Edmond D. Chow ,  Michinari Momma

IPC: G06F17/30

CPC classification number: G06Q30/06 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0204 ,  G06Q30/0224 ,  G06Q30/0605

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20090271245A1

公开(公告)日：2009-10-29

申请号：US12110171

申请日：2008-04-25

Applicant: Ashutosh Umakant Joshi ,  Zhenyu Yan ,  Marc-david Cohen ,  Shailesh Kumar

Inventor： Ashutosh Umakant Joshi ,  Zhenyu Yan ,  Marc-david Cohen ,  Shailesh Kumar

IPC: G06Q30/00

CPC classification number: G06Q30/02 ,  G06Q30/0202

Abstract: A computer-implemented method described for facilitating selection of an assortment of products to offer for sale. The method includes receiving transaction data representing characteristics of a plurality of commercial transactions including a first product and a second product. Product attribute data representing attributes for at least the two products are also received. Substitution demand data for the second product is estimated which represents demand for the second product given the first product is not available, the estimation being based on the transaction data and product attribute data.

Abstract translation: 描述了一种计算机实现的方法，用于促进选择提供出售的各种产品。 该方法包括接收表示包括第一产品和第二产品的多个商业交易的特征的交易数据。 还接收表示至少两个产品的属性的产品属性数据。 估计第二产品的替代需求数据，其代表第一产品不可用的第二产品的需求，该估计基于交易数据和产品属性数据。