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    • 56. 发明申请
    • MULTI-TENANCY DATA STORAGE AND ACCESS METHOD AND APPARATUS
    • 多元数据存储和访问方法和设备
    • US20100005055A1
    • 2010-01-07
    • US12493315
    • 2009-06-29
    • Wenhao AnBo GaoChang Jie GuoZhong SuWei SunZhi Hu WangZhen Zhang
    • Wenhao AnBo GaoChang Jie GuoZhong SuWei SunZhi Hu WangZhen Zhang
    • G06F17/30
    • G06F17/30448G06F17/30566
    • A method, apparatus, and a computer program product for storing and accessing multi-tenancy data. The method includes the steps of: creating a plurality of table sets in one or more databases, wherein each table set is used to store data of a group of tenants selected from a plurality of tenants; accessing data of a tenant in a table set in response to receiving a data access request from the tenant; and recording relationships between the tenants and the table sets in a multi-tenancy metadata repository, wherein the step of accessing the data of the tenant comprises the steps of finding the table set by querying the metadata repository and accessing the data of the tenant in the table set based on the result received from the query of the metadata repository.
    • 一种用于存储和访问多租户数据的方法,装置和计算机程序产品。 该方法包括以下步骤:在一个或多个数据库中创建多个表集合,其中每个表集合用于存储从多个租户中选择的一组租户的数据; 响应于从租户接收到数据访问请求,访问表中的租户的数据; 以及在多租户元数据存储库中记录所述租户和所述表集合之间的关系,其中,访问所述承租人的数据的步骤包括以下步骤:通过查询所述元数据存储库并访问所述租户的数据来查找所述表 基于从元数据存储库的查询获得的结果的表集合。
    • 60. 发明授权
    • System and methods for processing biological expression data
    • 用于处理生物表达数据的系统和方法
    • US07113896B2
    • 2006-09-26
    • US10144455
    • 2002-05-13
    • Zhen ZhangHong Zhang
    • Zhen ZhangHong Zhang
    • G06F17/10
    • G06F19/20G06Q10/0635
    • A system and method for processing information in a data set that contains samples of at least two classes using an empirical risk minimization model, wherein each sample in the data set has an importance score. In one embodiment, the method includes the step of selecting samples of a first class being labeled with class label +1 and a second class with class label −1, from the data set, prescribing an empirical risk minimization model using the selected samples with an objective function and a plurality of constraints which adequately describes the solution of a classifier to separate the selected samples into the first class and the second class, modifying the empirical risk minimization model to include terms that individually limit the influence of each sample relative to its importance score in the solution of the empirical risk minimization model, and solving the modified empirical risk minimization model to obtain the corresponding classifier to separate the samples into the first class and the second class.
    • 一种用于使用经验风险最小化模型来处理包含至少两个类别的样本的数据集中的信息的系统和方法,其中所述数据集中的每个样本具有重要性得分。 在一个实施例中,该方法包括以下步骤:从数据集中选择标记有类标号+1的第一类样本和具有类标号-1的第二类,使用所选择的样本规定经验风险最小化模型 目标函数和多个约束,其充分描述分类器的解决方案以将所选样本分离成第一类和第二类,将经验风险最小化模型修改为包括单独限制每个样本相对于其重要性的影响的项 在经验风险最小化模型的解中得分,并求解经修正的经验风险最小化模型,得到相应的分类器,将样本分为第一类和第二类。