专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US08086655B2 Methods and apparatus for perturbing an evolving data stream for time series compressibility and privacy 有权
标题翻译：扰乱不断发展的数据流的方法和装置，用于时间序列可压缩性和隐私
公开(公告)号：US08086655B2
公开(公告)日：2011-12-27
申请号：US11855378
申请日：2007-09-14
申请人： Philip Shi-Lung Yu , Spyridon Papadimitriou
发明人： Philip Shi-Lung Yu , Spyridon Papadimitriou
IPC分类号： G06F17/14
CPC分类号： G06N7/02 , G06F17/30539 , G16H50/70
摘要： Techniques for perturbing an evolving data stream are provided. The evolving data stream is received. An online linear transformation is applied to received values of the evolving data stream generating a plurality of transform coefficients. A plurality of significant transform coefficients are selected from the plurality of transform coefficients. Noise is embedded into each of the plurality of significant transform coefficients, thereby perturbing the evolving data stream. A total noise variance does not exceed a defined noise variance threshold.
摘要翻译：提供了扰乱演进数据流的技术。收到不断发展的数据流。在线线性变换被应用于产生多个变换系数的演进数据流的接收值。从多个变换系数中选择多个有效变换系数。噪声嵌入到多个有效变换系数中的每一个中，从而扰乱演进数据流。总噪声方差不超过定义的噪声方差阈值。

2. 发明授权

US07730364B2 Systems and methods for predictive failure management 有权
标题翻译：用于预测性故障管理的系统和方法
公开(公告)号：US07730364B2
公开(公告)日：2010-06-01
申请号：US11696795
申请日：2007-04-05
申请人： Shu-Ping Chang , Xiaohui Gu , Spyridon Papadimitriou , Philip Shi-lung Yu
发明人： Shu-Ping Chang , Xiaohui Gu , Spyridon Papadimitriou , Philip Shi-lung Yu
IPC分类号： G06F11/00
CPC分类号： G06F11/008 , G06F11/0709 , G06F11/0751 , H04L41/0663 , H04L41/147 , H04L43/022 , H04L43/0817
摘要： A system and method for using continuous failure predictions for proactive failure management in distributed cluster systems includes a sampling subsystem configured to continuously monitor and collect operation states of different system components. An analysis subsystem is configured to build classification models to perform on-line failure predictions. A failure prevention subsystem is configured to take preventive actions on failing components based on failure warnings generated by the analysis subsystem.
摘要翻译：用于在分布式集群系统中使用连续故障预测进行主动故障管理的系统和方法包括：被配置为连续监视和收集不同系统组件的操作状态的采样子系统。分析子系统被配置为构建分类模型以执行在线故障预测。故障预防子系统被配置为根据分析子系统生成的故障警告对故障组件采取预防措施。

3. 发明申请

US20080071843A1 Systems and methods for indexing and visualization of high-dimensional data via dimension reorderings 审中-公开
标题翻译：通过尺寸重排序对高维数据进行索引和可视化的系统和方法
公开(公告)号：US20080071843A1
公开(公告)日：2008-03-20
申请号：US11521141
申请日：2006-09-14
申请人： Spyridon Papadimitriou , Zografoula Vagena , Michail Vlachos , Philip Shi-lung Yu
发明人： Spyridon Papadimitriou , Zografoula Vagena , Michail Vlachos , Philip Shi-lung Yu
IPC分类号： G06F17/30
CPC分类号： G06F16/283
摘要： Systems and methods for reordering dimensions of a multiple-dimensional dataset includes ordering dimensions of multi-dimensional dataset such that original D dimensions of the data are reordered to obtain a smooth sequence representation which includes placement of the D dimensions with similar behavior at adjacent positions in an ordered sequence representation. The ordered sequence representation is segmented into groups of K
摘要翻译：用于重新排序多维数据集的尺寸的系统和方法包括多维数据集的排序维度，使得数据的原始D维度被重新排序以获得平滑序列表示，其包括在相邻位置处具有类似行为的D维的放置有序序列表示。有序序列表示被分割成K

4. 发明申请

US20090077148A1 Methods and Apparatus for Perturbing an Evolving Data Stream for Time Series Compressibility and Privacy 有权
标题翻译：扰动不断发展的数据流的时间序列压缩和隐私的方法和装置
公开(公告)号：US20090077148A1
公开(公告)日：2009-03-19
申请号：US11855378
申请日：2007-09-14
申请人： Philip Shi-Lung Yu , Spyridon Papadimitriou
发明人： Philip Shi-Lung Yu , Spyridon Papadimitriou
IPC分类号： G06F17/10 , G06F17/14
CPC分类号： G06N7/02 , G06F17/30539 , G16H50/70
摘要： Techniques for perturbing an evolving data stream are provided. The evolving data stream is received. An online linear transformation is applied to received values of the evolving data stream generating a plurality of transform coefficients. A plurality of significant transform coefficients are selected from the plurality of transform coefficients. Noise is embedded into each of the plurality of significant transform coefficients, thereby perturbing the evolving data stream. A total noise variance does not exceed a defined noise variance threshold.
摘要翻译：提供了扰乱演进数据流的技术。收到不断发展的数据流。在线线性变换被应用于产生多个变换系数的演进数据流的接收值。从多个变换系数中选择多个有效变换系数。噪声嵌入到多个有效变换系数中的每一个中，从而扰乱演进数据流。总噪声方差不超过定义的噪声方差阈值。

5. 发明申请

US20080250265A1 SYSTEMS AND METHODS FOR PREDICTIVE FAILURE MANAGEMENT 有权
标题翻译：预测失效管理系统与方法
公开(公告)号：US20080250265A1
公开(公告)日：2008-10-09
申请号：US11696795
申请日：2007-04-05
申请人： SHU-PING CHANG , Xiaohui Gu , Spyridon Papadimitriou , Philip Shi-lung Yu
发明人： SHU-PING CHANG , Xiaohui Gu , Spyridon Papadimitriou , Philip Shi-lung Yu
IPC分类号： G06F11/00
CPC分类号： G06F11/008 , G06F11/0709 , G06F11/0751 , H04L41/0663 , H04L41/147 , H04L43/022 , H04L43/0817
摘要： A system and method for using continuous failure predictions for proactive failure management in distributed cluster systems includes a sampling subsystem configured to continuously monitor and collect operation states of different system components. An analysis subsystem is configured to build classification models to perform on-line failure predictions. A failure prevention subsystem is configured to take preventive actions on failing components based on failure warnings generated by the analysis subsystem.
摘要翻译：用于在分布式集群系统中使用连续故障预测进行主动故障管理的系统和方法包括：被配置为连续监视和收集不同系统组件的操作状态的采样子系统。分析子系统被配置为构建分类模型以执行在线故障预测。故障预防子系统被配置为根据分析子系统生成的故障警告对故障组件采取预防措施。

6. 发明申请

US20070294247A1 Identifying optimal multi-scale patterns in time-series streams 审中-公开
标题翻译：确定时间序列流中的最优多尺度模式
公开(公告)号：US20070294247A1
公开(公告)日：2007-12-20
申请号：US11471002
申请日：2006-06-20
申请人： Spyridon Papadimitriou , Philip S. Yu
发明人： Spyridon Papadimitriou , Philip S. Yu
IPC分类号： G06F17/30
CPC分类号： G06K9/00496
摘要： A method, system, and computer readable medium for identifying local patterns in at least one time series data stream are disclosed. The method comprises generating multiple ordered levels of hierarchal approximation functions. The multiple ordered levels are generated directly from at least one given time series data stream including at least one set of time series data. The hierarchical approximation functions for each level of the multiple levels is based upon creating a set of approximating functions. The hierarchical approximation functions are also based upon selecting a current window with a current window length from a set of varying window lengths. The current window is selected for a current level of the multiple levels.
摘要翻译：公开了一种用于识别至少一个时间序列数据流中的局部模式的方法，系统和计算机可读介质。该方法包括生成层次近似函数的多个有序级别。多个有序级别直接从包括至少一组时间序列数据的至少一个给定时间序列数据流生成。多层次的每个级别的层次近似函数基于创建一组近似函数。层次近似函数还基于从一组变化的窗口长度中选择具有当前窗口长度的当前窗口。为当前级别选择当前窗口。

7. 发明授权

US07945570B2 Identifying optimal multi-scale patterns in time-series streams 失效
标题翻译：确定时间序列流中的最优多尺度模式
公开(公告)号：US07945570B2
公开(公告)日：2011-05-17
申请号：US12551033
申请日：2009-08-31
申请人： Spyridon Papadimitriou , Philip S. Yu
发明人： Spyridon Papadimitriou , Philip S. Yu
IPC分类号： G06F17/30
CPC分类号： G06K9/00496
摘要： A computer-implemented method, system, and a computer readable article of manufacture identify local patterns in at least one time series data stream. A data stream is received that comprises at least one set of time series data. The at least one set of time series data is formed into a set of multiple ordered levels of time series data. Multiple ordered levels of hierarchical approximation functions are generated directly from the multiple ordered levels of time series data. A set of approximating functions are created for each level. A current window with a current window length is selected from a set of varying window lengths. The set of approximating functions created at one level in the multiple ordered levels is passed to a subsequent level as a set of time series data. The multiple ordered levels of hierarchical approximation functions are stored into memory after being generated.
摘要翻译：计算机实现的方法，系统和计算机可读制造商标识至少一个时间序列数据流中的局部模式。接收包括至少一组时间序列数据的数据流。至少一组时间序列数据被形成为一组时间序列数据的多个有序级别。分层近似函数的多个有序级别直接从多个有序级别的时间序列数据生成。为每个级别创建一组近似函数。从一组变化的窗口长度中选择具有当前窗口长度的当前窗口。在多个有序等级中在一个级别创建的一组近似函数作为一组时间序列数据传递到后续级别。分层近似函数的多个有序等级在生成后被存储到存储器中。

8. 发明授权

US07483934B1 Methods involving computing correlation anomaly scores 失效
标题翻译：涉及计算相关异常评分的方法
公开(公告)号：US07483934B1
公开(公告)日：2009-01-27
申请号：US11959073
申请日：2007-12-18
申请人： Tsuyoshi Ide , Spyridon Papadimitriou
发明人： Tsuyoshi Ide , Spyridon Papadimitriou
IPC分类号： G06F17/15
CPC分类号： G06K9/00979 , G06K9/6224 , G06K9/6284
摘要： An exemplary method for computing correlation anomaly scores, including, defining a first similarity matrix for a target run of data, the target run of data includes an N number of sensors, defining a second similarity matrix for a reference run of data, the target run of data includes the N number of sensors, developing a k-neighborhood graph Ni of the i-th node for the target run of data, wherein the k-neighborhood graph of the i-th node is defined as a graph comprising the i-th node and its k-nearest neighbors (NN), developing a k-neighborhood graph Ni of the i-th node for the reference run of data, defining a probability distribution p(j|i), wherein p(j|i) is the probability that the j-th node becomes one of the k-NN of the i-th node, coupling the probability between the i-th node and the neighbors of the i-th node, determining an anomaly score of the i-th node, and determining whether the target run of data has changed from the reference run of data responsive to determining the anomaly score of the i-th node.
摘要翻译：一种用于计算相关异常评分的示例性方法，包括定义目标数据运行的第一相似度矩阵，目标数据运行包括N个传感器，为参考数据运行定义第二相似矩阵，目标运行的数据包括N个传感器，为目标运行数据开发第i个节点的k邻域图Ni，其中第i个节点的k邻域图被定义为包括i- （NN），为参考运行数据开发第i个节点的k邻域图，其定义概率分布p（j | i）其中p（j | i）是第j个节点成为第i个节点的k-NN之一的概率，将第i个节点与第i个节点的邻居之间的概率相耦合，确定第i个节点的异常分数，并确定数据的目标运行是否已经从参考运行的数据响应t o确定第i个节点的异常得分。

9. 发明申请

US20110055379A1 CONTENT-BASED AND TIME-EVOLVING SOCIAL NETWORK ANALYSIS 有权
标题翻译：基于内容和时间演化的社会网络分析
公开(公告)号：US20110055379A1
公开(公告)日：2011-03-03
申请号：US12552812
申请日：2009-09-02
申请人： Ching-Yung Lin , Spyridon Papadimitriou , Jimeng Sun , Kun-Lung Wu
发明人： Ching-Yung Lin , Spyridon Papadimitriou , Jimeng Sun , Kun-Lung Wu
IPC分类号： G06F17/10 , G06F15/173
CPC分类号： G06K9/00677 , G06K9/6224 , G06Q30/02
摘要： System and method for modeling a content-based network. The method includes finding single mode clusters from among network (sender and recipient) and content dimensions represented as a tensor data structure. The method allows for derivation of useful cross-mode clusters (interpretable patterns) that reveal key relationships among user communities and keyword concepts for presentation to users in a meaningful and intuitive way. Additionally, the derivation of useful cross-mode clusters is facilitated by constructing a reduced low-dimensional representation of the content-based network. Moreover, the invention may be enhanced for modeling and analyzing the time evolution of social communication networks and the content related to such networks. To this end, a set of non-overlapping or possibly overlapping time-based windows is constructed and the analysis performed at each successive time interval.
摘要翻译：用于建模基于内容的网络的系统和方法。该方法包括从网络（发送者和接收者）和表示为张量数据结构的内容维度中找到单一模式集群。该方法允许推导出有用的交叉模式集群（可解释模式），其显示用户社区之间的关键关系和关键字概念，以有意义和直观的方式呈现给用户。另外，通过构建基于内容的网络的减少的低维表示来促进有用的交叉模式集群的推导。此外，本发明可以被增强用于建模和分析社交通信网络的时间演进和与这样的网络有关的内容。为此，构建一组不重叠或可能重叠的基于时间的窗口，并且在每个连续的时间间隔执行分析。

10. 发明授权

US07840516B2 Preserving privacy of one-dimensional data streams by perturbing data with noise and using dynamic autocorrelation 失效
标题翻译：通过噪声干扰数据并使用动态自相关来保护一维数据流的隐私
公开(公告)号：US07840516B2
公开(公告)日：2010-11-23
申请号：US11678808
申请日：2007-02-26
申请人： Yuan-Chi Chang , Feifei Li , Spyridon Papadimitriou , George A. Mihaila , Ioana Stanoi , Jimeng Sun , Philip S. Yu
发明人： Yuan-Chi Chang , Feifei Li , Spyridon Papadimitriou , George A. Mihaila , Ioana Stanoi , Jimeng Sun , Philip S. Yu
IPC分类号： G06F17/00
CPC分类号： G06F21/755
摘要： A method, information processing system, and computer readable medium are provided for preserving privacy of one-dimensional nonstationary data streams. The method includes receiving a one-dimensional nonstationary data stream. A set of first-moment statistical values are calculated, for a given instant of sub-space of time, for the data. The first moment statistical values include a principal component for the sub-space of time. The data is perturbed with noise along the principal component in proportion to the first-moment of statistical values so that at least part of a set of second-moment statistical values for the data is perturbed by the noise only within a predetermined variance.
摘要翻译：提供了一种方法，信息处理系统和计算机可读介质，用于保持一维非平稳数据流的隐私。该方法包括接收一维非平稳数据流。对于数据的子时间空间的给定时刻，计算一组一阶统计值。第一时刻统计值包括时间子空间的主成分。数据按照与主要分量成比例的噪声与第一时刻的统计值相互扰动，使得数据的至少一部分二阶统计值仅在预定方差内被噪声扰动。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式