SYSTEMS AND METHODS FOR CHARACTERIZING LINKED DOCUMENTS USING A LATENT TOPIC MODEL
    1.
    发明申请
    SYSTEMS AND METHODS FOR CHARACTERIZING LINKED DOCUMENTS USING A LATENT TOPIC MODEL 有权
    使用专利主题模型表征链接文档的系统和方法

    公开(公告)号:US20100161611A1

    公开(公告)日:2010-06-24

    申请号:US12629043

    申请日:2009-12-01

    IPC分类号: G06F17/30 G06F15/18 G06N5/04

    CPC分类号: G06N7/005 G06F17/30014

    摘要: Systems and methods are disclosed for extracting characteristics from a corpus of linked documents by deriving a content link model that explicitly captures direct and indirect relations represented by the links, and extracting document topics and the topic distributions for all the documents in the corpus using the content-link model.

    摘要翻译: 公开了系统和方法,用于通过导出显式地捕获由链接表示的直接和间接关系的内容链接模型,以及使用内容来提取语料库中的所有文档的文档主题和主题分布来从链接文档的语料库中提取特征 链接模型。

    Systems and methods for characterizing linked documents using a latent topic model
    2.
    发明授权
    Systems and methods for characterizing linked documents using a latent topic model 有权
    使用潜在主题模型来表征链接文档的系统和方法

    公开(公告)号:US08234274B2

    公开(公告)日:2012-07-31

    申请号:US12629043

    申请日:2009-12-01

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06N7/005 G06F17/30014

    摘要: Systems and methods are disclosed for extracting characteristics from a corpus of linked documents by deriving a content link model that explicitly captures direct and indirect relations represented by the links, and extracting document topics and the topic distributions for all the documents in the corpus using the content-link model.

    摘要翻译: 公开了系统和方法,用于通过导出显式地捕获由链接表示的直接和间接关系的内容链接模型,以及使用内容来提取语料库中的所有文档的文档主题和主题分布来从链接文档的语料库中提取特征 链接模型。

    Admission control in cloud databases under service level agreements
    3.
    发明授权
    Admission control in cloud databases under service level agreements 有权
    根据服务级别协议在云数据库中进行接纳控制

    公开(公告)号:US08768875B2

    公开(公告)日:2014-07-01

    申请号:US13251215

    申请日:2011-10-01

    摘要: An admission control system for a cloud database includes a machine learning prediction module to estimate a predicted probability for a newly arrived query with a deadline, if admitted into the cloud database, to finish its execution before said deadline, wherein the prediction considers query characteristics and current system conditions. The system also includes a decision module applying the predicted probability to admit a query into the cloud database with a target of profit maximization with an expected profit determined using one or more service level agreements (SLAs).

    摘要翻译: 用于云数据库的准入控制系统包括:机器学习预测模块,用于在所述截止期限之前估计具有截止日期的新到达查询的预测概率(如果被允许进入云数据库)以完成其执行,其中所述预测考虑查询特性, 当前系统条件。 该系统还包括一个决策模块,将预测的概率应用于使用一个或多个服务水平协议(SLA)确定的预期利润的利润最大化目标的云数据库中进行查询。

    Intelligent management of virtualized resources for cloud database systems
    4.
    发明授权
    Intelligent management of virtualized resources for cloud database systems 有权
    云数据库系统虚拟化资源的智能管理

    公开(公告)号:US08359223B2

    公开(公告)日:2013-01-22

    申请号:US12985021

    申请日:2011-01-05

    IPC分类号: G06Q10/00 G06F15/18 G06N5/02

    摘要: Systems and methods are disclosed to manage resources in a cloud-based computing system by generating a model of a relationship between cloud database resources and an expected profit based on cloud-server system parameters and service level agreements (SLAs) that indicates profits for different system performances, wherein the model comprises a two level optimization/control problem, wherein model receives system metrics, number of replicas, and arrival rate as the multiple input; and dynamically adjusting resource allocation among different customers based on current customer workload and the expected profit to maximize the expected profit for a cloud computing service provider.

    摘要翻译: 披露了系统和方法来管理云计算系统中的资源,通过生成云数据库资源之间的关系模型和基于云服务器系统参数和服务水平协议(SLA)的预期利润,该协议指示不同系统的利润 性能,其中模型包括两级优化/控制问题,其中模型接收系统度量,复制数量和到达速率作为多输入; 并根据当前客户工作量和预期利润动态调整不同客户之间的资源配置,以最大化云计算服务提供商的预期利润。

    Processing high-dimensional data via EM-style iterative algorithm
    5.
    发明授权
    Processing high-dimensional data via EM-style iterative algorithm 有权
    通过EM型迭代算法处理高维数据

    公开(公告)号:US08099381B2

    公开(公告)日:2012-01-17

    申请号:US12199912

    申请日:2008-08-28

    IPC分类号: G06F7/60 G06F17/10

    CPC分类号: G06F17/30592

    摘要: Systems and methods are disclosed for factorizing high-dimensional data by simultaneously capturing factors for all data dimensions and their correlations in a factor model, wherein the factor model provides a parsimonious description of the data; and generating a corresponding loss function to evaluate the factor model.

    摘要翻译: 公开了系统和方法,用于通过在因子模型中同时捕获所有数据维及其相关性的因子来分解高维数据,其中因子模型提供数据的简约描述; 并产生相应的损失函数来评估因子模型。

    Portable workload performance prediction for the cloud
    8.
    发明授权
    Portable workload performance prediction for the cloud 有权
    云的便携式工作负载性能预测

    公开(公告)号:US09111232B2

    公开(公告)日:2015-08-18

    申请号:US13874769

    申请日:2013-05-01

    IPC分类号: G06F15/18 G06N99/00 G06N5/04

    CPC分类号: G06N99/005 G06N5/04

    摘要: Systems and methods are disclosed to perform performance prediction for cloud-based databases by building on a computer a cloud database performance model using a set of training workloads; and using a learned model on the computer to predict database performance in the cloud for a new workload, wherein for each reference workload r and hardware configuration h, system throughput tr,h, average throughput of αr and standard deviation σr, comprising normalizing each throughput as: t r , h _ = t r , h - a r σ r .

    摘要翻译: 披露了系统和方法,通过使用一组训练工作负载,在计算机上构建云数据库性能模型,来对云数据库执行性能预测; 并在计算机上使用学习模型来预测云中的新工作负载的数据库性能,其中对于每个参考工作负载r和硬件配置h,系统吞吐量tr,h,αr的平均吞吐量和标准偏差r包括归一化 每个吞吐量如下:tr,h _ = tr,h-ar&sgr; r。

    Social network analysis with prior knowledge and non-negative tensor factorization
    9.
    发明授权
    Social network analysis with prior knowledge and non-negative tensor factorization 有权
    社会网络分析与先验知识和非负张量分解

    公开(公告)号:US08346708B2

    公开(公告)日:2013-01-01

    申请号:US12469043

    申请日:2009-05-20

    IPC分类号: G06F9/44 G06N7/02 G06N7/06

    CPC分类号: G06Q30/02

    摘要: Systems and methods are disclosed to analyze a social network by generating a data tensor from social networking data; applying a non-negative tensor factorization (NTF) with user prior knowledge and preferences to generate a core tensor and facet matrices; and rendering information to social networking users based on the core tensor and facet matrices.

    摘要翻译: 公开了通过从社交网络数据生成数据张量来分析社交网络的系统和方法; 应用具有用户先验知识和偏好的非负张量因子分解(NTF)来生成核心张量和小平面矩阵; 并基于核心张量和面矩阵将信息呈现给社交网络用户。

    ADMISSION CONTROL IN CLOUD DATABASES UNDER SERVICE LEVEL AGREEMENTS
    10.
    发明申请
    ADMISSION CONTROL IN CLOUD DATABASES UNDER SERVICE LEVEL AGREEMENTS 有权
    服务水平协议下的云数据库入门管制

    公开(公告)号:US20120109873A1

    公开(公告)日:2012-05-03

    申请号:US13251215

    申请日:2011-10-01

    IPC分类号: G06N7/02

    摘要: An admission control system for a cloud database includes a machine learning prediction module to estimate a predicted probability for a newly arrived query with a deadline, if admitted into the cloud database, to finish its execution before said deadline, wherein the prediction considers query characteristics and current system conditions. The system also includes a decision module applying the predicted probability to admit a query into the cloud database with a target of profit maximization with an expected profit determined using one or more service level agreements (SLAs).

    摘要翻译: 用于云数据库的准入控制系统包括:机器学习预测模块,用于在所述截止期限之前估计具有截止日期的新到达查询的预测概率(如果被允许进入云数据库)以完成其执行,其中所述预测考虑查询特性, 当前系统条件。 该系统还包括一个决策模块,将预测的概率应用于使用一个或多个服务水平协议(SLA)确定的预期利润的利润最大化目标的云数据库中进行查询。