利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

18 条记录 (耗时 0.019 秒)

    Systems and methods of partitioning data for synchronous parallel processing
    1.
    发明授权
    Systems and methods of partitioning data for synchronous parallel processing 有权
    用于同步并行处理的数据分区系统和方法

    公开(公告)号：US08429165B1

    公开(公告)日：2013-04-23

    申请号：US13413978

    申请日：2012-03-07

    申请人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam ,  Tridib Mukherjee

    发明人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam ,  Tridib Mukherjee

    IPC分类号： G06F17/30

    CPC分类号： G06F9/505 ,  G06F17/3089

    摘要： Methods and systems for partitioning data for processing in a plurality of data centers are disclosed. For each of a plurality of data centers, a time period required for the data center to process an amount of information may be estimated. The plurality of data centers may be ordered based on the time period for each data center. Data may be received from one or more sources. A data center having a smallest time period from the ordered plurality of data centers may be selected to be added to a set of data centers. An overall execution time for the set of data centers to process the data may be determined. The selecting and determining operations may be repeated until the overall execution time satisfies one or more threshold criteria. The data may be transmitted to the set of data centers.

    摘要翻译： 公开了用于分割用于在多个数据中心中进行处理的数据的方法和系统。 对于多个数据中心中的每一个，可以估计数据中心处理信息量所需的时间段。 可以基于每个数据中心的时间段来排序多个数据中心。 可以从一个或多个来源接收数据。 可以选择具有来自有序多个数据中心的最小时间周期的数据中心以被添加到一组数据中心。 可以确定用于处理数据的数据中心集合的总执行时间。 可以重复选择和确定操作，直到总体执行时间满足一个或多个阈值标准。 数据可以被发送到数据中心集合。

    SYSTEMS AND METHODS FOR BEHAVIORAL PATTERN MINING
    2.
    发明申请
    SYSTEMS AND METHODS FOR BEHAVIORAL PATTERN MINING 有权
    用于行为图案采矿的系统和方法

    公开(公告)号：US20130346447A1

    公开(公告)日：2013-12-26

    申请号：US13529111

    申请日：2012-06-21

    申请人： Changjun Wu ,  Shanmuga-Nathan Gnanasambandam ,  Gueyoung Jung ,  Shi Zhao

    发明人： Changjun Wu ,  Shanmuga-Nathan Gnanasambandam ,  Gueyoung Jung ,  Shi Zhao

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30876 ,  G06F17/30867

    摘要： Methods and systems of performing data mining may include receiving a plurality of web log records and a plurality of call log records; associating one or more web log records with a call log record, wherein the associated user for each of the associated one or more web log records and the call log record are the same; identifying one or more patterns among the web log records for the plurality of call log records, wherein each pattern comprises one or more web accesses, a time stamp at which each of the one or more web accesses is performed and the call topic for the call log record; identifying one or more web log records associated with a new call, and predicting a call topic for the new call based on at least one pattern and the one or more web log records.

    摘要翻译： 执行数据挖掘的方法和系统可以包括接收多个web日志记录和多个呼叫记录记录; 将一个或多个Web日志记录与呼叫记录记录相关联，其中，所述相关联的一个或多个web日志记录中的每一个的关联用户和所述呼叫记录记录是相同的; 识别用于多个呼叫记录记录的web日志记录中的一个或多个模式，其中每个模式包括一个或多个web访问，执行一个或多个web访问中的每一个执行的时间戳以及用于呼叫的呼叫主题 日志记录; 识别与新呼叫相关联的一个或多个web日志记录，以及基于至少一个模式和所述一个或多个web日志记录来预测新呼叫的呼叫主题。

    Systems and methods for behavioral pattern mining
    4.
    发明授权
    Systems and methods for behavioral pattern mining 有权
    行为模式挖掘的系统和方法

    公开(公告)号：US09305104B2

    公开(公告)日：2016-04-05

    申请号：US13529111

    申请日：2012-06-21

    申请人： Changjun Wu ,  Shanmuga-Nathan Gnanasambandam ,  Gueyoung Jung ,  Shi Zhao

    发明人： Changjun Wu ,  Shanmuga-Nathan Gnanasambandam ,  Gueyoung Jung ,  Shi Zhao

    IPC分类号： G06F7/00 ,  G06F17/00 ,  G06F17/30

    CPC分类号： G06F17/30876 ,  G06F17/30867

    摘要： Methods and systems of performing data mining may include receiving a plurality of web log records and a plurality of call log records; associating one or more web log records with a call log record, wherein the associated user for each of the associated one or more web log records and the call log record are the same; identifying one or more patterns among the web log records for the plurality of call log records, wherein each pattern comprises one or more web accesses, a time stamp at which each of the one or more web accesses is performed and the call topic for the call log record; identifying one or more web log records associated with a new call, and predicting a call topic for the new call based on at least one pattern and the one or more web log records.

    摘要翻译： 执行数据挖掘的方法和系统可以包括接收多个web日志记录和多个呼叫记录记录; 将一个或多个Web日志记录与呼叫记录记录相关联，其中，所述相关联的一个或多个web日志记录中的每一个的关联用户和所述呼叫记录记录是相同的; 识别用于所述多个呼叫记录记录的所述web日志记录中的一个或多个模式，其中每个模式包括一个或多个web访问，执行所述一个或多个web访问中的每一个的时间戳以及所述呼叫的呼叫话题 日志记录; 识别与新呼叫相关联的一个或多个web日志记录，以及基于至少一个模式和所述一个或多个web日志记录来预测新呼叫的呼叫主题。

    Systems and methods for self-adaptive episode mining under the threshold using delay estimation and temporal division
    5.
    发明授权
    Systems and methods for self-adaptive episode mining under the threshold using delay estimation and temporal division 有权
    使用延迟估计和时间分割在阈值下进行自适应事件挖掘的系统和方法

    公开(公告)号：US08965830B2

    公开(公告)日：2015-02-24

    申请号：US13474083

    申请日：2012-05-17

    申请人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam

    发明人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam

    IPC分类号： G06F17/00 ,  G06N5/02

    CPC分类号： G06F17/30539

    摘要： Embodiments relate to systems and methods for self-adaptive episode mining under time threshold using delay estimation and temporal division. An episode mining engine can analyze a set of episodes captured from a set of network resources to detect all sequences of user-specified frequency within a supplied runtime budget or time threshold. The engine can achieve desired levels of completeness in the results by mining the input log file in multiple stages or steps, each having successively longer lengths of event sequences. After completion of each stage, the engine calculates a remaining amount of runtime budget, and updates the amount of time to be allocated for each of the remaining stages up to a generated maximum stage (or sequence length). The engine thus corrects the estimated remaining time in the runtime budget (or threshold) after each stage, and continues to the next stage until the runtime budget is consumed.

    摘要翻译： 实施例涉及使用延迟估计和时间划分在时间阈值下进行自适应事件挖掘的系统和方法。 情节挖掘引擎可以分析从一组网络资源捕获的一组剧集，以检测所提供的运行时预算或时间阈值内的用户指定频率的所有序列。 引擎可以通过以多个阶段或步骤挖掘输入日志文件来获得所需结果的完整性，每个步骤具有连续更长的事件序列长度。 在每个阶段完成之后，引擎计算运行时间预算的剩余量，并且更新要分配给每个剩余阶段的时间直到生成的最大阶段（或序列长度）。 因此，引擎在每个阶段之后校正运行时间预算（或阈值）中的估计剩余时间，并且继续下一阶段，直到运行时预算消耗。

    SYSTEMS AND METHODS FOR SELF-ADAPTIVE EPISODE MINING UNDER THE THRESHOLD USING DELAY ESTIMATION AND TEMPORAL DIVISION
    6.
    发明申请
    SYSTEMS AND METHODS FOR SELF-ADAPTIVE EPISODE MINING UNDER THE THRESHOLD USING DELAY ESTIMATION AND TEMPORAL DIVISION 有权
    使用延迟估计和时间段在自适应阈值下进行自适应压缩采矿的系统和方法

    公开(公告)号：US20130311994A1

    公开(公告)日：2013-11-21

    申请号：US13474083

    申请日：2012-05-17

    申请人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam

    发明人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam

    IPC分类号： G06F9/46

    CPC分类号： G06F17/30539

    摘要： Embodiments relate to systems and methods for self-adaptive episode mining under time threshold using delay estimation and temporal division. An episode mining engine can analyze a set of episodes captured from a set of network resources to detect all sequences of user-specified frequency within a supplied runtime budget or time threshold. The engine can achieve desired levels of completeness in the results by mining the input log file in multiple stages or steps, each having successively longer lengths of event sequences. After completion of each stage, the engine calculates a remaining amount of runtime budget, and updates the amount of time to be allocated for each of the remaining stages up to a generated maximum stage (or sequence length). The engine thus corrects the estimated remaining time in the runtime budget (or threshold) after each stage, and continues to the next stage until the runtime budget is consumed.

    摘要翻译： 实施例涉及使用延迟估计和时间划分在时间阈值下进行自适应事件挖掘的系统和方法。 情节挖掘引擎可以分析从一组网络资源捕获的一组剧集，以检测所提供的运行时预算或时间阈值内的用户指定频率的所有序列。 引擎可以通过以多个阶段或步骤挖掘输入日志文件来获得所需结果的完整性，每个步骤具有连续更长的事件序列长度。 在每个阶段完成之后，引擎计算运行时间预算的剩余量，并且更新要分配给每个剩余阶段的时间直到生成的最大阶段（或序列长度）。 因此，引擎在每个阶段之后校正运行时间预算（或阈值）中的估计剩余时间，并且继续下一阶段，直到运行时预算消耗。

    METHODS AND SYSTEMS FOR SCALABLE EXTRACTION OF EPISODE RULES USING INCREMENTAL EPISODE TREE CONSTRUCTION IN A MULTI-APPLICATION EVENT SPACE
    7.
    发明申请
    METHODS AND SYSTEMS FOR SCALABLE EXTRACTION OF EPISODE RULES USING INCREMENTAL EPISODE TREE CONSTRUCTION IN A MULTI-APPLICATION EVENT SPACE 有权
    在多应用事件空间中使用增加的EPISODE树构造可扩展提取EPISODE规则的方法和系统

    公开(公告)号：US20130110758A1

    公开(公告)日：2013-05-02

    申请号：US13284356

    申请日：2011-10-28

    申请人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam ,  Andres Quiroz Hernandez ,  Zhiguo Li

    发明人： Gueyoung Jung ,  Shanmuga-Nathan Gnanasambandam ,  Andres Quiroz Hernandez ,  Zhiguo Li

    IPC分类号： G06N5/02

    CPC分类号： G06N99/005 ,  G06N5/025 ,  G06N5/04

    摘要： Methods and systems for scalable extraction of episode rules using incremental episode tree construction in a multi-application event space comprise compiling events from multiple, different domain logs into in a universal log file, rolling domain-dependent and domain-independent windows through the universal log file to identify distinct event-pattern episodes, adding episodes to an episode tree data structure, pruning less frequent episodes from the episode tree, analyzing the episode tree to identify frequent episode rules, and applying the frequent episode rules to future interactions with users.

    摘要翻译： 在多应用程序事件空间中使用增量插曲树构造可扩展提取剧集规则的方法和系统包括将多个不同域日志中的事件从通用日志文件中编译，通过通用日志滚动域依赖和不依赖域的窗口 文件以识别不同的事件模式情节，将剧集添加到情节树数据结构，从情节树中修剪较少频繁的剧集，分析情节树以识别频繁的剧集规则，以及将频繁剧集规则应用于与用户的未来交互。

    Method and system for collaborative self-organization of devices
    8.
    发明授权
    Method and system for collaborative self-organization of devices 有权
    设备协同自组织的方法和系统

    公开(公告)号：US08645514B2

    公开(公告)日：2014-02-04

    申请号：US11382107

    申请日：2006-05-08

    申请人： Shanmuga-Nathan Gnanasambandam ,  Tracy E. Thieret ,  Naveen Sharma

    发明人： Shanmuga-Nathan Gnanasambandam ,  Tracy E. Thieret ,  Naveen Sharma

    IPC分类号： G06F15/177 ,  G06F15/173 ,  G06F1/24 ,  G06F9/00

    CPC分类号： G06Q10/06

    摘要： Methods and systems for automatically organizing devices in a network are disclosed. Information may be collected for a plurality of devices in a predetermined area over a predetermined period of time. The information may include device location information and device information for one or more user groups. Each user group may include one or more users. An average preference for each user group may be determined for each device based on the device usage information. The plurality of devices may be organized automatically into a plurality of clusters based on at least the determined average preferences. Each cluster may include one or more devices.

    摘要翻译： 公开了用于在网络中自动组织设备的方法和系统。 可以在预定时间段内为预定区域中的多个设备收集信息。 信息可以包括用于一个或多个用户组的设备位置信息和设备信息。 每个用户组可以包括一个或多个用户。 可以基于设备使用信息为每个设备确定每个用户组的平均偏好。 至少基于所确定的平均偏好，多个设备可以自动组织成多个集群。 每个集群可以包括一个或多个设备。

    METHOD AND SYSTEM FOR COLLABORATIVE SELF-ORGANIZATION OF DEVICES
    9.
    发明申请
    METHOD AND SYSTEM FOR COLLABORATIVE SELF-ORGANIZATION OF DEVICES 有权
    设备协同自组织的方法与系统

    公开(公告)号：US20070260716A1

    公开(公告)日：2007-11-08

    申请号：US11382107

    申请日：2006-05-08

    申请人： Shanmuga-Nathan Gnanasambandam ,  Tracy Thieret ,  Naveen Sharma

    发明人： Shanmuga-Nathan Gnanasambandam ,  Tracy Thieret ,  Naveen Sharma

    IPC分类号： G06F15/173

    CPC分类号： G06Q10/06

    摘要： Methods and systems for automatically organizing devices in a network are disclosed. Information may be collected for a plurality of devices in a predetermined area over a predetermined period of time. The information may include device location information and device information for one or more user groups. Each user group may include one or more users. An average preference for each user group may be determined for each device based on the device usage information. The plurality of devices may be organized automatically into a plurality of clusters based on at least the determined average preferences. Each cluster may include one or more devices.

    摘要翻译： 公开了用于在网络中自动组织设备的方法和系统。 可以在预定时间段内为预定区域中的多个设备收集信息。 信息可以包括用于一个或多个用户组的设备位置信息和设备信息。 每个用户组可以包括一个或多个用户。 可以基于设备使用信息为每个设备确定对每个用户组的平均偏好。 至少基于所确定的平均偏好，多个设备可以自动组织成多个集群。 每个集群可以包括一个或多个设备。