System and method for classifying data streams using high-order models
    1.
    发明授权
    System and method for classifying data streams using high-order models 有权
    使用高阶模型对数据流进行分类的系统和方法

    公开(公告)号:US07724784B2

    公开(公告)日:2010-05-25

    申请号:US11520529

    申请日:2006-09-13

    IPC分类号: H04J3/04

    CPC分类号: H04L65/601 H04L65/607

    摘要: A computer implemented method, system, and computer usable program code for classifying a data stream using high-order models. The data stream is divided into a plurality of data segments. A classifier is selected for each of the plurality of data segments. Each of a plurality of classifiers is clustered into states. A state transition matrix is computed for the states. The states of the state transition matrix specify one of the high-order models for classifying the data stream.

    摘要翻译: 计算机实现的方法,系统和计算机可用程序代码,用于使用高阶模型对数据流进行分类。 数据流被分成多个数据段。 为多个数据段中的每一个选择分类器。 多个分类器中的每一个被聚类成状态。 为状态计算状态转换矩阵。 状态转换矩阵的状态指定用于对数据流进行分类的高阶模型之一。

    METHOD AND SYSTEM FOR MINIMAL DETOUR ROUTING WITH MULTIPLE STOPS
    2.
    发明申请
    METHOD AND SYSTEM FOR MINIMAL DETOUR ROUTING WITH MULTIPLE STOPS 审中-公开
    用于多台机器的最小转移路由的方法和系统

    公开(公告)号:US20080275646A1

    公开(公告)日:2008-11-06

    申请号:US11743784

    申请日:2007-05-03

    IPC分类号: G01C21/32 G05D1/00

    摘要: The present invention provides a system and method for optimizing routes that include multiple stops. This is accomplished by allowing users to identify a starting point, a destination, and types of businesses or other locations to be visited along the way. A route processor then provides users with a list of stores or other requested detour choices yielding a trip of optimal itinerary. The detour choices may be either an ordered sequence or an unordered set of points to be visited and may include constraints that make it possible to optimize utility functions according to user preferences.

    摘要翻译: 本发明提供了一种用于优化包括多个站点的路由的系统和方法。 这是通过允许用户识别出发点,目的地和商业类型或其他要访问的位置来实现的。 然后,路由处理器向用户提供商店列表或其他请求的绕行选择,产生最佳行程的行程。 绕行选择可以是要访问的有序序列或无序的点集合,并且可以包括使得可以根据用户偏好优化效用函数的约束。

    System and method for classifying data streams using high-order models
    3.
    发明申请
    System and method for classifying data streams using high-order models 有权
    使用高阶模型对数据流进行分类的系统和方法

    公开(公告)号:US20080126556A1

    公开(公告)日:2008-05-29

    申请号:US11520529

    申请日:2006-09-13

    IPC分类号: G06F15/16

    CPC分类号: H04L65/601 H04L65/607

    摘要: A computer implemented method, system, and computer usable program code for classifying a data stream using high-order models. The data stream is divided into a plurality of data segments. A classifier is selected for each of the plurality of data segments. Each of a plurality of classifiers is clustered into states. A state transition matrix is computed for the states. The states of the state transition matrix specify one of the high-order models for classifying the data stream.

    摘要翻译: 计算机实现的方法,系统和计算机可用程序代码,用于使用高阶模型对数据流进行分类。 数据流被分成多个数据段。 为多个数据段中的每一个选择分类器。 多个分类器中的每一个被聚类成状态。 为状态计算状态转换矩阵。 状态转换矩阵的状态指定用于对数据流进行分类的高阶模型之一。

    Query integrity assurance in database outsourcing
    4.
    发明申请
    Query integrity assurance in database outsourcing 有权
    查询数据库外包的完整性保证

    公开(公告)号:US20080183656A1

    公开(公告)日:2008-07-31

    申请号:US11626847

    申请日:2007-01-25

    IPC分类号: G06F17/30

    摘要: A method, system and computer program product for confirming the validity of data returned from a data store. A data store contains a primary data set encrypted using a first encryption and a secondary data set using a second encryption. The secondary data set is a subset of the primary data set. A client issues a substantive query against the data store to retrieve a primary data result belonging to the primary data set. A query interface issues at least one validating query against the data store. Each validating query returns a secondary data result belonging to the secondary data set. The query interface receives the secondary data result and provides a data invalid notification if data satisfying the substantive query included in an unencrypted form of the secondary data result is not contained in an unencrypted form of the primary data result.

    摘要翻译: 一种用于确认从数据存储返回的数据的有效性的方法,系统和计算机程序产品。 数据存储包含使用第一加密加密的主数据集和使用第二加密的辅数据集。 辅助数据集是主数据集的子集。 客户端对数据存储器发出实质性查询以检索属于主数据集的主数据结果。 查询界面对数据存储区发出至少一个验证查询。 每个验证查询返回属于辅助数据集的辅助数据结果。 如果满足辅助数据结果的未加密形式的实质性查询的数据未包含在主数据结果的未加密形式中,则查询接口接收辅助数据结果并提供数据无效通知。

    METHOD FOR FAST RELEVANCE DISCOVERY IN TIME SERIES
    5.
    发明申请
    METHOD FOR FAST RELEVANCE DISCOVERY IN TIME SERIES 有权
    时间序列中快速相关发现的方法

    公开(公告)号:US20080177813A1

    公开(公告)日:2008-07-24

    申请号:US11563900

    申请日:2006-11-28

    IPC分类号: G06F17/15

    CPC分类号: G06K9/00536

    摘要: A method for measuring time series relevance using state transition points, including inputting time series data and relevance threshold data. Then convert all time series values to ranks within [0,1] interval. Calculate the valid range of the transition point in [0,1]. Afterwards, a verification occurs that a time series Z exists for each pair of time series Z and Y, such that the relevances between X and Z, and between Y and Z are known. Then deduce the relevance of X and Y. The relevance of X and Y must be at least one of, (i) higher, and (ii) lower than, the given threshold. Provided Z is found terminate all remaining calculations for X and Y. Otherwise, segment the time series if no Z time series exists, use the segmented time series to estimate the relevance. Apply a hill climbing algorithm in the valid range to find the true relevance.

    摘要翻译: 一种使用状态转换点来测量时间序列相关性的方法,包括输入时间序列数据和相关阈值数据。 然后将所有时间序列值转换为[0,1]间隔内的等级。 计算[0,1]中转换点的有效范围。 之后,对于每对时间序列Z和Y存在时间序列Z的验证,使得X和Z之间,以及Y和Z之间的相关性是已知的。 然后推导X和Y的相关性.X和Y的相关性必须至少为(i)较高和(ii)低于给定阈值中的一个。 如果Z被找到终止X和Y的所有剩余计算。否则,如果没有Z时间序列,则分段时间序列,使用分段时间序列来估计相关性。 在有效范围内应用爬山算法来找到真正的相关性。

    System and method of mining time-changing data streams using a dynamic rule classifier having low granularity
    6.
    发明授权
    System and method of mining time-changing data streams using a dynamic rule classifier having low granularity 失效
    使用具有低粒度的动态规则分类器挖掘时变数据流的系统和方法

    公开(公告)号:US07720785B2

    公开(公告)日:2010-05-18

    申请号:US12121942

    申请日:2008-05-16

    IPC分类号: G06N5/02

    CPC分类号: G06N5/025

    摘要: A dynamic rule classifier for mining a data stream includes at least one window for viewing data contained in the data stream and a set of rules for mining the data. Rules are added and the set of rules are updated by algorithms when an drift in a concept within the data occurs, causing unacceptable drops in classification accuracy. The dynamic rule classifier is also implemented as a method and a computer program product.

    摘要翻译: 用于挖掘数据流的动态规则分类器包括用于查看数据流中包含的数据的至少一个窗口和用于挖掘数据的一组规则。 添加规则,并且当数据中的概念中的漂移发生时,通过算法更新规则集合,导致分类准确性的不可接受的下降。 动态规则分类器也被实现为一种方法和一种计算机程序产品。

    SYSTEM AND METHOD OF MINING TIME-CHANGING DATA STREAMS USING A DYNAMIC RULE CLASSIFIER HAVING LOW GRANULARITY
    7.
    发明申请
    SYSTEM AND METHOD OF MINING TIME-CHANGING DATA STREAMS USING A DYNAMIC RULE CLASSIFIER HAVING LOW GRANULARITY 审中-公开
    使用具有低精度的动态规则分类器来采集时变数据流的系统和方法

    公开(公告)号:US20070260568A1

    公开(公告)日:2007-11-08

    申请号:US11379692

    申请日:2006-04-21

    IPC分类号: G06N5/02

    CPC分类号: G06N5/025

    摘要: A dynamic rule classifier for mining a data stream includes at least one window for viewing data contained in the data stream and a set of rules for mining the data. Rules are added and the set of rules are updated by algorithms when an drift in a concept within the data occurs, causing unacceptable drops in classification accuracy. The dynamic rule classifier is also implemented as a method and a computer program product.

    摘要翻译: 用于挖掘数据流的动态规则分类器包括用于查看数据流中包含的数据的至少一个窗口和用于挖掘数据的一组规则。 添加规则,并且当数据中的概念中的漂移发生时,通过算法更新规则集合,导致分类准确性的不可接受的下降。 动态规则分类器也被实现为一种方法和一种计算机程序产品。

    Methods and apparatus for mining attribute associations
    8.
    发明授权
    Methods and apparatus for mining attribute associations 失效
    挖掘属性关联的方法和装置

    公开(公告)号:US07243100B2

    公开(公告)日:2007-07-10

    申请号:US10630992

    申请日:2003-07-30

    IPC分类号: G06F17/30 G06F17/00

    摘要: Attribute association discovery techniques that support relational-based data mining are disclosed. In one aspect of the invention, a technique for mining attribute associations in a relational data set comprises the following steps/operations. Multiple items are obtained from the relational data set. Then, attribute associations are discovered using: (i) multi-attribute mining templates formed from at least a portion of the multiple items; and (ii) one or more mining preferences specified by a user. The invention provides a novel architecture for the mining search space so as to exploit the inter-relationships among patterns of different templates. The framework is relational-sensitive and supports interactive and online mining.

    摘要翻译: 公开了支持基于关系的数据挖掘的属性关联发现技术。 在本发明的一个方面,用于挖掘关系数据集中的属性关联的技术包括以下步骤/操作。 从关系数据集获得多个项目。 然后,使用以下方式发现属性关联:(i)由多个项目的至少一部分形成的多属性挖掘模板; 和(ii)用户指定的一个或多个挖掘偏好。 本发明提供了一种用于挖掘搜索空间的新型架构,以便利用不同模板的模式之间的相互关系。 该框架是关系敏感的,支持交互式和在线挖掘。

    System and method for indexing weighted-sequences in large databases
    9.
    发明授权
    System and method for indexing weighted-sequences in large databases 有权
    用于索引大数据库中加权序列的系统和方法

    公开(公告)号:US09009176B2

    公开(公告)日:2015-04-14

    申请号:US12198717

    申请日:2008-08-26

    IPC分类号: G06F7/00 G06F17/30

    摘要: The present invention provides an index structure for managing weighted-sequences in large databases. A weighted-sequence is defined as a two-dimensional structure in which each element in the sequence is associated with a weight. A series of network events, for instance, is a weighted-sequence because each event is associated with a timestamp. Querying a large sequence database by events' occurrence patterns is a first step towards understanding the temporal causal relationships among the events. The index structure proposed herein enables the efficient retrieval from the database of all subsequences (contiguous and non-contiguous) that match a given query sequence both by events and by weights. The index structure also takes into consideration the nonuniform frequency distribution of events in the sequence data.

    摘要翻译: 本发明提供了一种用于在大数据库中管理加权序列的索引结构。 加权序列被定义为二维结构,其中序列中的每个元素与权重相关联。 例如,一系列网络事件是加权序列,因为每个事件都与时间戳相关联。 通过事件发生模式查询大序列数据库是了解事件之间的时间因果关系的第一步。 这里提出的索引结构使得能够通过事件和权重从数据库有效地检索与给定查询序列匹配的所有子序列(连续的和不连续的)。 索引结构还考虑了序列数据中事件的不均匀频率分布。

    Integrity assurance of query result from database service provider
    10.
    发明授权
    Integrity assurance of query result from database service provider 有权
    数据库服务提供商的查询结果的完整性保证

    公开(公告)号:US07870398B2

    公开(公告)日:2011-01-11

    申请号:US11626847

    申请日:2007-01-25

    IPC分类号: G06F12/14 G06F7/00

    摘要: A method, system and computer program product for confirming the validity of data returned from a data store. A data store contains a primary data set encrypted using a first encryption and a secondary data set using a second encryption. The secondary data set is a subset of the primary data set. A client issues a substantive query against the data store to retrieve a primary data result belonging to the primary data set. A query interface issues at least one validating query against the data store. Each validating query returns a secondary data result belonging to the secondary data set. The query interface receives the secondary data result and provides a data invalid notification if data satisfying the substantive query included in an unencrypted form of the secondary data result is not contained in an unencrypted form of the primary data result.

    摘要翻译: 一种用于确认从数据存储返回的数据的有效性的方法,系统和计算机程序产品。 数据存储包含使用第一加密加密的主数据集和使用第二加密的辅数据集。 辅助数据集是主数据集的子集。 客户端对数据存储器发出实质性查询以检索属于主数据集的主数据结果。 查询界面对数据存储区发出至少一个验证查询。 每个验证查询返回属于辅助数据集的辅助数据结果。 如果满足辅助数据结果的未加密形式的实质性查询的数据未包含在主数据结果的未加密形式中,则查询接口接收辅助数据结果并提供数据无效通知。