公开(公告)号：US08055532B2

公开(公告)日：2011-11-08

申请号：US11396612

申请日：2006-04-04

Applicant: Wanli Min ,  Aleksandra Mojsilovic

Inventor： Wanli Min ,  Aleksandra Mojsilovic

IPC: G06Q30/00

CPC classification number: G06Q30/02 ,  G06Q10/0631 ,  G06Q10/06311 ,  G06Q30/0204 ,  G06Q30/0241 ,  G06Q40/00

Abstract: A method of thresholding of a database of customer purchasing history using a computer, includes providing a customer purchase history database including data regarding customer satisfaction, awareness of vendor brands, previous purchasing history, and size of customer budget, providing a predetermined threshold regarding the data, establishing, in the computer, boundaries surrounding the predetermined threshold, splitting the data, in the computer, to maximize the differences in the data across the split; generating, in the computer, a model of the data, in the computer, based upon the split, and allocating marketing resources based upon the model.

Abstract translation: 使用计算机对客户采购历史数据库进行阈值化的方法包括提供客户购买历史数据库，其中包括关于客户满意度的信息，供应商品牌的意识，先前的采购历史和客户预算的大小，提供关于数据的预定阈值 在计算机中建立围绕预定阈值的边界，在计算机中分割数据以最大化跨越分割的数据的差异; 在计算机中，在计算机中基于分割生成数据的模型，并基于模型分配营销资源。

公开(公告)号：US07831868B2

公开(公告)日：2010-11-09

申请号：US12062270

申请日：2008-04-03

Applicant: Kathryn Allyn Bassin ,  Wanli Min ,  Bonnie Kathryn Ray ,  Padmanabhan Santhanam

Inventor： Kathryn Allyn Bassin ,  Wanli Min ,  Bonnie Kathryn Ray ,  Padmanabhan Santhanam

IPC: G06F11/00

CPC classification number: G06Q10/06

Abstract: A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.

Abstract translation: 一种方法和系统基于先前对支持请求的观察的统计模型来估计未来的软件支持需求，对于相同的产品或具有先前识别为与新产品的特征相关的特征的不同产品。 估计数包括支持请求的估计数量和估计类型的支持请求。 估计的类型包括在故障时发生的活动，关于软件中的缺陷以前是否已知的标识符等。 估计用于在接收到支持请求之前以及软件产品发布之前估计和分配支持资源。

公开(公告)号：US07509163B1

公开(公告)日：2009-03-24

申请号：US11863586

申请日：2007-09-28

Applicant: Gang Luo ,  Wanli Min

Inventor： Gang Luo ,  Wanli Min

IPC: A61B5/05

CPC classification number: G06K9/00536 ,  A61B5/0476 ,  A61B5/16 ,  A61B5/4812 ,  A61B5/7267

Abstract: A method of subject-adaptive, real-time sleep stage classification to classify electroencephalogram sleep recordings into sleep stages to determine whether a subject exhibits a sleep disorder includes performing subject adaptation to improve classification accuracy for a new subject with limited training data, the performing subject adaptation comprises using linear-chain conditional random fields and potential functions, training the linear-chain conditional random fields using the training data, continuously receiving the electroencephalogram waves, continuously extracting features from the electroencephalogram waves, the extracting features comprising transforming each of the electroencephalogram waves to capture information embedded in the electroencephalogram waves, and continuously classifying the sleep stages according to extracted features and learned parameters from the linear-chain conditional random fields.

Abstract translation: 一种主题适应性实时睡眠阶段分类方法，将脑电图睡眠记录分类到睡眠阶段，以确定受试者是否表现出睡眠障碍，包括进行受试者适应，以提高具有有限训练数据的新受试者的分类准确性， 适应包括使用线性链条件随机场和潜在函数，使用训练数据训练线性链条件随机场，连续接收脑电波，从脑电波中连续提取特征，提取特征包括变换每个脑电波 捕获嵌入在脑电波中的信息，并且根据提取的特征和来自线性链条件随机场的学习参数来连续分类睡眠阶段。

公开(公告)号：US20080215401A1

公开(公告)日：2008-09-04

申请号：US12062802

申请日：2008-04-04

Applicant: Feng Cheng ,  David Garnarnik ,  Wanli Min ,  Bala Ramachandran ,  Jonathan Miles Collin Rosenoer

Inventor： Feng Cheng ,  David Garnarnik ,  Wanli Min ,  Bala Ramachandran ,  Jonathan Miles Collin Rosenoer

IPC: G06Q10/00

CPC classification number: G06Q40/08 ,  G06Q10/0631 ,  G06Q10/06312 ,  G06Q10/0635 ,  G06Q10/06375 ,  G06Q30/0201 ,  G06Q40/025

Abstract: Risk in business management is analyzed based on a probabilistic network approach which quantifies the impact of operational risk on financial metrics such as Value-at-Risk (VAR) and/or Potential Losses (PL). This approach provides further capability to determine the optimal placement of one or more countermeasures within a system to minimize the impact of operational risks.

Abstract translation: 基于概率网络方法来分析业务管理风险，该方法量化了操作风险对诸如风险价值（VAR）和/或潜在损失（PL）等财务指标的影响。 这种方法提供了进一步的能力来确定系统内的一个或多个对策的最佳布置以最小化操作风险的影响。

公开(公告)号：US10733573B2

公开(公告)日：2020-08-04

申请号：US15551187

申请日：2016-02-04

Applicant: Alibaba Group Holding Limited ,  Yu Wang ,  Rui Wang ,  Jinming Wang ,  Jiqiu Xu ,  Weiwei Fu ,  Wanli Min

Inventor： Yu Wang ,  Rui Wang ,  Jinming Wang ,  Jiqiu Xu ,  Weiwei Fu ,  Wanli Min

IPC: G06Q10/10 ,  G06Q40/00 ,  G06Q10/06

Abstract: The disclosed embodiments describe a method, apparatus, and system for pushing information. In one embodiment, the method comprises: receiving dynamic spatio-temporal behavior data of a moving individual; conducting an analysis according to historical dynamic spatio-temporal behavior data of the moving individual to acquire spatio-temporal behavioral characteristics of the moving individual; determining appropriate information as matching information for the moving individual according to the spatio-temporal behavioral characteristics of the moving individual in combination with dynamic spatio-temporal behavior data of the moving individual at a current time; and sending the matching information to the moving individual. In the method of the disclosure, behavioral characteristics of a moving individual are analyzed to obtain habit and preference characteristics of the moving individual. Targeted push information is sent, thereby solving the problem of pushed information having less diversified, targeted, and not so accurate content.

公开(公告)号：US07953544B2

公开(公告)日：2011-05-31

申请号：US11626592

申请日：2007-01-24

Applicant: Yasuo Amemiya ,  Wanli Min ,  Laura Wynter

Inventor： Yasuo Amemiya ,  Wanli Min ,  Laura Wynter

IPC: G06F19/00 ,  G06G7/70 ,  G06G7/76 ,  G08G1/00

CPC classification number: G08G1/0104

Abstract: A method and structure for predicting traffic on a network, includes a receiver which receives data related to traffic on at least a portion of a network. A calculator calculates a traffic prediction for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network.

Abstract translation: 一种用于预测网络上的业务的方法和结构，包括在网络的至少一部分上接收与业务有关的数据的接收机。 计算器计算网络的至少一部分的流量预测，通过使用与网络上的历史流量的偏差来计算流量预测。

公开(公告)号：US20110040532A1

公开(公告)日：2011-02-17

申请号：US12540213

申请日：2009-08-12

Applicant: Hendrik F. Hamann ,  Raymond Lloyd ,  Wanli Min

Inventor： Hendrik F. Hamann ,  Raymond Lloyd ,  Wanli Min

IPC: G06F17/10 ,  G06G7/56

CPC classification number: G06F1/206 ,  H05K7/20836

Abstract: Techniques for data center analysis are provided. In one aspect, a method for modeling thermal distributions in a data center is provided. The method includes the following steps. Vertical temperature distribution data is obtained for a plurality of locations throughout the data center. The vertical temperature distribution data for each of the locations is plotted as an s-curve, wherein the vertical temperature distribution data reflects physical conditions at each of the locations which is reflected in a shape of the s-curve. Each of the s-curves is represented with a set of parameters that characterize the shape of the s-curve, wherein the s-curve representations make up a knowledge base model of predefined s-curve types from which thermal distributions and associated physical conditions at the plurality of locations throughout the data center can be analyzed.

Abstract translation: 提供数据中心分析技术。 在一方面，提供了一种用于对数据中心中的热分布建模的方法。 该方法包括以下步骤。 在整个数据中心的多个位置获得垂直的温度分布数据。 每个位置的垂直温度分布数据被绘制为s曲线，其中垂直温度分布数据反映了以s曲线的形状反映的每个位置处的物理条件。 每个s曲线用表征s曲线形状的一组参数表示，其中s曲线表示构成了预定义的s曲线类型的知识库模型，其中热分布和相关联的物理条件 可以分析整个数据中心的多个位置。

公开(公告)号：US07765436B2

公开(公告)日：2010-07-27

申请号：US11449735

申请日：2006-06-09

Applicant: Kathryn Allyn Bassin ,  Wanli Min ,  Bonnie Kathryn Ray ,  Padmanabhan Santhanam

Inventor： Kathryn Allyn Bassin ,  Wanli Min ,  Bonnie Kathryn Ray ,  Padmanabhan Santhanam

IPC: G06F11/00

CPC classification number: G06Q10/06

Abstract: A method and system estimates future software support requirements based on statistical models of previous observations of support requests, either for the same product or for a different product having features previously identified as correlated with features of a new product. The estimates include an estimated volume of support requests and an estimated type of support requests. The estimated types include the activity occurring at the time of the failure, an identifier as to whether a defect in the software was previously known, and the like. The estimates are used to estimate and allocate support resources prior to support requests being received, and prior to a software product being released.

公开(公告)号：US20090088658A1

公开(公告)日：2009-04-02

申请号：US11863586

申请日：2007-09-28

Applicant: Gang Luo ,  Wanli Min

Inventor： Gang Luo ,  Wanli Min

IPC: A61B5/04

CPC classification number: G06K9/00536 ,  A61B5/0476 ,  A61B5/16 ,  A61B5/4812 ,  A61B5/7267

Abstract: A method of subject-adaptive, real-time sleep stage classification to classify electroencephalogram sleep recordings into sleep stages to determine whether a subject exhibits a sleep disorder includes performing subject adaptation to improve classification accuracy for a new subject with limited training data, the performing subject adaptation comprises using linear-chain conditional random fields and potential functions, training the linear-chain conditional random fields using the training data, continuously receiving the electroencephalogram waves, continuously extracting features from the electroencephalogram waves, the extracting features comprising transforming each of the electroencephalogram waves to capture information embedded in the electroencephalogram waves, and continuously classifying the sleep stages according to extracted features and learned parameters from the linear-chain conditional random fields.

Abstract translation: 一种主题适应性实时睡眠阶段分类方法，将脑电图睡眠记录分类到睡眠阶段，以确定受试者是否表现出睡眠障碍，包括进行受试者适应，以提高具有有限训练数据的新受试者的分类准确性， 适应包括使用线性链条件随机场和潜在函数，使用训练数据训练线性链条件随机场，连续接收脑电波，从脑电波中连续提取特征，提取特征包括变换每个脑电波 捕获嵌入在脑电波中的信息，并且根据提取的特征和来自线性链条件随机场的学习参数来连续分类睡眠阶段。

公开(公告)号：US20070208600A1

公开(公告)日：2007-09-06

申请号：US11364158

申请日：2006-03-01

Applicant: Steven Babus ,  Wanli Min ,  Bala Ramachandran ,  Jonathan Rosenoer

Inventor： Steven Babus ,  Wanli Min ,  Bala Ramachandran ,  Jonathan Rosenoer

IPC: G06F9/44

CPC classification number: G06Q10/04 ,  G06Q10/0635 ,  G06Q30/0202

Abstract: A computer implemented method and a computer system implementing the method provide enterprises with pre-emptive/proactive operational risk management. First, historical data on the occurrence of operational risk events and other internal business/external metrics and indicators are collected. This is followed by construction of a model for correlating the risk events with internal and external metrics and indicators. This can result in the estimation of the probability of occurrence of risk events and a model for the severity of a loss event (in termns of, say, dollar amount) as a function of the various variables that are related to or have leverage on the business operation. The Key Risk Indicators for the business are then identified based on the model. Following this, the identified key risk factors are forecasted for future time periods and used to identify early warnings of risk and is further validated. This is used as a basis for the identification and execution of appropriate proactive/pre-emptive risk management and mitigation actions.

Abstract translation: 计算机实现的方法和实施该方法的计算机系统为企业提供先发制人/主动操作风险管理。 首先收集关于操作风险事件发生的历史数据和其他内部业务/外部指标和指标。 随后，建立一个将风险事件与内部和外部指标和指标相关联的模型。 这可以导致风险事件的发生概率的估计和损失事件的严重程度的模型（例如，例如，美元金额）作为与相关或具有杠杆作用的各种变量的函数 商业运营。 然后根据模型确定业务的主要风险指标。 此后，确定的关键风险因素预测未来时间段，并用于识别早期的风险预警，并进一步验证。 这被用作识别和执行适当的主动/先发制人的风险管理和缓解行动的基础。