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    Database configuration analysis
    1.
    发明授权
    Database configuration analysis 有权
    数据库配置分析

    公开(公告)号：US07805443B2

    公开(公告)日：2010-09-28

    申请号：US11275657

    申请日：2006-01-20

    申请人： Arnd Christian Konig ,  Shubha Umesh Nabar

    发明人： Arnd Christian Konig ,  Shubha Umesh Nabar

    IPC分类号： G06F7/00

    CPC分类号： G06F17/30306

    摘要： To determine a configuration for a database system, a plurality of queries may be sampled from a representative workload using statistical inference to compute the probability of correctly selecting one of a plurality of evaluation configurations. The probability of correctly selecting may determine which and/or how many queries to sample, and/or may be compared to a target probability threshold to determine if more queries must be sampled. The configuration from the plurality of configurations with the lowest estimated cost of executing the representative workload may be determined based on the probability of selecting correctly. Estimator variance may be reduced through a stratified sampling scheme that leverages commonality, such as an average cost of execution, between queries based on query templates. The applicability of the Central Limit Theorem may be verified and used to determine which and/or how many queries to sample.

    摘要翻译： 为了确定数据库系统的配置，可以使用统计推断从代表性工作负载中采样多个查询，以计算正确选择多个评估配置之一的概率。 正确选择的概率可以确定要采样和/或可以与目标概率阈值进行比较和/或可以查询多少查询以确定是否必须对更多查询进行采样。 可以基于正确选择的概率来确定具有执行代表性工作负荷的估计成本最低的多个配置的配置。 通过分层采样方案，可以通过分层抽样方案来减少估计器差异，该方案利用基于查询模板的查询之间的共同性，如平均执行成本。 可以验证中心极限定理的适用性，并用于确定哪些和/或多少查询查询。

    DATABASE CONFIGURATION ANALYSIS
    3.
    发明申请
    DATABASE CONFIGURATION ANALYSIS 有权
    数据库配置分析

    公开(公告)号：US20070174335A1

    公开(公告)日：2007-07-26

    申请号：US11275657

    申请日：2006-01-20

    申请人： Arnd Konig ,  Shubha Umesh Nabar

    发明人： Arnd Konig ,  Shubha Umesh Nabar

    IPC分类号： G06F17/00 ,  G06F7/00

    CPC分类号： G06F17/30306

    摘要： To determine a configuration for a database system, a plurality of queries may be sampled from a representative workload using statistical inference to compute the probability of correctly selecting one of a plurality of evaluation configurations. The probability of correctly selecting may determine which and/or how many queries to sample, and/or may be compared to a target probability threshold to determine if more queries must be sampled. The configuration from the plurality of configurations with the lowest estimated cost of executing the representative workload may be determined based on the probability of selecting correctly. Estimator variance may be reduced through a stratified sampling scheme that leverages commonality, such as an average cost of execution, between queries based on query templates. The applicability of the Central Limit Theorem may be verified and used to determine which and/or how many queries to sample.

    摘要翻译： 为了确定数据库系统的配置，可以使用统计推断从代表性工作负载中采样多个查询，以计算正确选择多个评估配置之一的概率。 正确选择的概率可以确定要采样和/或可以与目标概率阈值进行比较和/或可以查询多少查询以确定是否必须对更多查询进行采样。 可以基于正确选择的概率来确定具有执行代表性工作负荷的估计成本最低的多个配置的配置。 通过分层采样方案，可以通过分层抽样方案来减少估计器差异，该方案利用基于查询模板的查询之间的共同性，如平均执行成本。 可以验证中心极限定理的适用性，并用于确定哪些和/或多少查询查询。

    Ranking Authors in Social Media Systems
    4.
    发明申请
    Ranking Authors in Social Media Systems 有权
    社交媒体系统排名作者

    公开(公告)号：US20120117059A1

    公开(公告)日：2012-05-10

    申请号：US12942577

    申请日：2010-11-09

    申请人： Peter Richard Bailey ,  Chad Carson ,  Scott Joseph Counts ,  Nikhil Bharat Dandekar ,  Ho John Lee ,  Shubha Umesh Nabar ,  Aditya Pal ,  Michael Ching ,  Paul Alexander Dow ,  Shuang Guo ,  Hyun-Ju Seo

    发明人： Peter Richard Bailey ,  Chad Carson ,  Scott Joseph Counts ,  Nikhil Bharat Dandekar ,  Ho John Lee ,  Shubha Umesh Nabar ,  Aditya Pal ,  Michael Ching ,  Paul Alexander Dow ,  Shuang Guo ,  Hyun-Ju Seo

    IPC分类号： G06F17/30

    CPC分类号： G06Q50/01 ,  G06F17/30867

    摘要： The author ranking technique described herein is a technique to rank authors in social media systems along various dimensions, using a variety of statistical methods for utilizing those dimensions. More particularly, the technique ranks authors in social media systems through a combination of statistical techniques that leverage usage metrics, and social and topical graph characteristics. In various exemplary embodiments, the technique can rank author authority by the following: 1) temporal analysis of link sharing in which authority is computed based on a user's propensity to provide early links to web pages that subsequently become popular; 2) topical authority based on the author's links and content updates in specific topic areas; and 3) popularity and influence based on nodal properties of authors.

    摘要翻译： 本文描述的作者排名技术是使用各种统计方法来利用这些维度来对各社会媒体系统中的作者进行各种维度的技术。 更具体地说，该技术通过结合利用使用度量的统计技术以及社会和局部图形特征来对社交媒体系统中的作者进行排名。 在各种示例性实施例中，该技术可以通过以下方式对作者权限进行排名：1）基于用户提供对随后变得流行的网页的早期链接的倾向来计算权限的链路共享的时间分析; 2）基于作者在特定主题领域的链接和内容更新的专题权威; 和3）基于作者的节点属性的人气和影响。