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    • 2. 发明授权
    • Systems and methods for data coding, transmission, storage and decoding
    • 用于数据编码,传输,存储和解码的系统和方法
    • US08321465B2
    • 2012-11-27
    • US11274821
    • 2005-11-14
    • Emanuel FarberScott HalsteadMichael J. HardinPaul Crispin Williams
    • Emanuel FarberScott HalsteadMichael J. HardinPaul Crispin Williams
    • G06F17/30
    • G06Q40/00
    • Systems and methods are provided for the provision of data for transmission and/or storage, the transmission and storage of data, and, more particularly, to data coding for transmission and/or storage and to decoding of received and/or accessed or retrieved coded data. In an embodiment of the invention, data is assembled into coded data structures comprising a plurality of fields that, e.g., may contain actual or implied field values, and data associated therewith that relates to the plurality of fields. Encoding and decoding of the data may take place with reference to one or more associated data models, and a coded data structure according to this embodiment may contain content only (field values and data identifying the structure). This allows for a reduction in size of the data structure as compared to, e.g., a data structure comprising program code or all data needed to describe the data in the data structure.
    • 提供了用于提供用于传输和/或存储的数据,数据的传输和存储的数据的系统和方法,更具体地,涉及用于传输和/或存储的数据编码以及对已接收和/或访问或检索的编码 数据。 在本发明的一个实施例中,将数据组装成包括多个场的编码数据结构,所述多个场例如可以包含实际或隐含的场值,以及与其相关联的与多个场相关的数据。 数据的编码和解码可以参考一个或多个相关联的数据模型进行,并且根据本实施例的编码数据结构可以仅包含内容(字段值和识别结构的数据)。 与例如包括描述数据结构中的数据所需的程序代码或所需数据的数据结构相比,这允许数据结构的尺寸减小。
    • 4. 发明授权
    • Method for analyzing sets of temporal data
    • 分析时间数据集的方法
    • US06571198B1
    • 2003-05-27
    • US09554359
    • 2000-07-10
    • Stephen E. BrossetteStephen A. MoserAlan P. SpragueMichael J. HardinWarren T. Jones
    • Stephen E. BrossetteStephen A. MoserAlan P. SpragueMichael J. HardinWarren T. Jones
    • G06F15177
    • G06F17/18G16H50/80Y10S707/99936
    • A method for analyzing sets of temporal data using a computer wherein each set of temporal data includes a plurality of records collected at a time unique to each such set and in which each record has a plurality of data items. The method includes the first step of creating data association rules for at least a plurality of sequential sets wherein each association rule represents data records having at least some common data items (100). A confidence factor is then determined for each such association rule and these confidence factors are stored in data partitions for the temporal data sets (102). The confidence factors for a selected data partition is then compared with the corresponding confidence factors of at least one other data partition (112), if available. When the confidence factor for the selected data partition varies from the corresponding confidence factor for the at least one other data partition exceeds a threshold value, an alert output signal is generated (114).
    • 一种用于使用计算机分析时间数据集合的方法,其中每组时间数据包括在每个这样的集合唯一的时间收集的多个记录,并且其中每个记录具有多个数据项。 该方法包括为至少多个顺序集创建数据关联规则的第一步骤,其中每个关联规则表示具有至少一些公共数据项(100)的数据记录。 然后确定每个这样的关联规则的置信因子,并且将这些置信因子存储在时间数据集(102)的数据分区中。 然后将所选择的数据分区的置信因子与至少一个其他数据分区(112)的相应置信因子进行比较(112)(如果可用)。 当所选择的数据分区的置信因子与至少一个其他数据分区的相应的置信因子变化超过阈值时,生成报警输出信号(114)。
    • 5. 发明授权
    • Method for analyzing sets of temporal data
    • 分析时间数据集的方法
    • US06574583B1
    • 2003-06-03
    • US09679676
    • 2000-10-05
    • Stephen E. BrossetteStephen A. MoserAlan P. SpragueMichael J. HardinWarren T. Jones
    • Stephen E. BrossetteStephen A. MoserAlan P. SpragueMichael J. HardinWarren T. Jones
    • G06F15177
    • G06Q10/04G06Q10/06G06Q40/08Y10S707/99936
    • A method for analyzing sets of temporal data using a computer is described. Each set of temporal data includes a plurality of records collected at a time unique to each such set and in which each record has a plurality of data items. The method includes the first step of creating data association rules for at least a plurality of sequential data sets wherein each association rule describes data items that are found together in some data records. An incidence proportion is then determined for each such association rule for each temporal data set and these incidence proportions are stored. The incidence proportions for each association rule are grouped into two aggregate proportions by a user defined window schedule that describes one or more pairs of a current window wc and a past window wp. The cumulative incidence proportions for each association rule for each past window wp are compared with the cumulative incidence proportion for the corresponding current window wc by a statistical test of two proportions. When the cumulative incidence proportion of the current window wc differs significantly from the corresponding cumulative incidence proportion of the past window wp, an event is generated. From the set of events generated, alerts are generated using a method called event capture. These alerts are presented to the user.
    • 描述了使用计算机分析时间数据集合的方法。 每组时间数据包括在每个这样的集合唯一的时间收集的多个记录,并且其中每个记录具有多个数据项。 该方法包括为至少多个顺序数据集创建数据关联规则的第一步骤,其中每个关联规则描述在一些数据记录中一起找到的数据项。 然后针对每个时间数据集的每个这样的关联规则确定发生比例,并存储这些发生比例。 通过描述一对或多对当前窗口wc和过去窗口wp的用户定义的窗口调度,将每个关联规则的发生比例分组为两个聚合比例。 通过两个比例的统计检验将每个过去窗口wp的每个关联规则的累积发生比例与相应的当前窗口wc的累积发生率进行比较。 当当前窗口wc的累积发生比例与过去窗口wp的相应累积发生比例显着不同时,会产生一个事件。 从生成的事件集中,使用称为事件捕获的方法生成警报。 这些警报会显示给用户。