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61. 发明申请

US20070239982A1 Method and apparatus for variable privacy preservation in data mining 审中-公开
标题翻译：数据挖掘中可变隐私保护的方法和装置
公开(公告)号：US20070239982A1
公开(公告)日：2007-10-11
申请号：US11249647
申请日：2005-10-13
申请人： Charu Aggarwal , Philip Yu
发明人： Charu Aggarwal , Philip Yu
IPC分类号： H04N7/16 , H04L9/32 , H04L9/00 , G06F12/14 , G06F17/30 , G06F7/04 , G06F11/30 , G06K9/00 , H03M1/68 , H04K1/00
CPC分类号： G06F21/604 , G06F21/6245 , G06F21/6254
摘要： Improved privacy preservation techniques are disclosed for use in accordance with data mining. By way of example, a technique for preserving privacy of data records for use in a data mining application comprises the following steps/operations. Different privacy levels are assigned to the data records. Condensed groups are constructed from the data records based on the privacy levels, wherein summary statistics are maintained for each condensed group. Pseudo-data is generated from the summary statistics, wherein the pseudo-data is available for use in the data mining application. Principles of the invention are capable of handling both static and dynamic data sets
摘要翻译：公开了根据数据挖掘使用的改进的隐私保护技术。作为示例，用于保留用于数据挖掘应用的数据记录的隐私的技术包括以下步骤/操作。不同的隐私级别被分配给数据记录。基于隐私级别的数据记录构建简化组，其中为每个缩合组维护概要统计。从摘要统计生成伪数据，其中伪数据可用于数据挖掘应用程序。本发明的原理能够处理静态和动态数据集

62. 发明申请

US20070226264A1 System and method for real-time materialized view maintenance 审中-公开
标题翻译：用于实时物化视图维护的系统和方法
公开(公告)号：US20070226264A1
公开(公告)日：2007-09-27
申请号：US11386346
申请日：2006-03-22
申请人： Gang Luo , Philip Yu
发明人： Gang Luo , Philip Yu
IPC分类号： G06F17/30
CPC分类号： G06F16/24535 , G06F16/2453 , G06F16/24539
摘要： There are provided a method, a computer program product, and a system for maintaining a materialized view defined on a relation of a relational database. The method includes the step of performing content-based filtering on the relation to identify an update to the relation as being irrelevant with respect to the materialized view.
摘要翻译：提供了一种方法，计算机程序产品和用于维护根据关系数据库的关系定义的物化视图的系统。该方法包括对关系执行基于内容的过滤以将关系的更新识别为与物化视图无关的步骤。

63. 发明申请

US20070226216A1 Methods and Apparatus for Dynamic Classification of Data in Evolving Data Stream 失效
标题翻译：数据流动态分类方法与装置
公开(公告)号：US20070226216A1
公开(公告)日：2007-09-27
申请号：US11756227
申请日：2007-05-31
申请人： Charu Aggarwal , Philip Yu
发明人： Charu Aggarwal , Philip Yu
IPC分类号： G06F7/00
CPC分类号： G06F17/30516 , G06F17/30598 , Y10S707/99942 , Y10S707/99943
摘要： A technique for classifying data from a test data stream is provided. A stream of training data having class labels is received. One or more class-specific clusters of the training data are determined and stored. At least one test instance of the test data stream is classified using the one or more class-specific clusters.
摘要翻译：提供了一种从测试数据流中分类数据的技术。接收具有类标签的训练数据流。确定并存储训练数据的一个或多个类特定的簇。测试数据流的至少一个测试实例使用一个或多个类特定簇进行分类。

64. 发明申请

US20070226209A1 Methods and Apparatus for Clustering Evolving Data Streams Through Online and Offline Components 审中-公开
标题翻译：通过在线和离线组件聚合演进数据流的方法和设备
公开(公告)号：US20070226209A1
公开(公告)日：2007-09-27
申请号：US11755473
申请日：2007-05-30
申请人： Charu Aggarwal , Philip Yu
发明人： Charu Aggarwal , Philip Yu
IPC分类号： G06F17/30
CPC分类号： G06F16/24568 , G06F16/285 , Y10S707/99931 , Y10S707/99943
摘要： A technique of clustering data of a data stream is provided. Online statistics are first created from the data stream. Offline processing of the online statistics is then performed when offline processing either required or desired. Online statistics may be created through the reception of data points from the data stream and the formation and updating of data groups. Offline processing may be performed by reclustering groups of data points around sampled data points and reporting the newly formed clusters.
摘要翻译：提供了一种数据流数据聚类技术。在线统计信息首先从数据流创建。然后，当离线处理需要或需要时，执行脱机处理在线统计信息。可以通过从数据流接收数据点以及数据组的形成和更新来创建在线统计。离线处理可以通过重新聚集采样数据点周围的数据点组并报告新形成的簇来执行。

65. 发明申请

US20070223598A1 Resource adaptive spectrum estimation of streaming data 有权
标题翻译：流数据资源自适应频谱估计
公开(公告)号：US20070223598A1
公开(公告)日：2007-09-27
申请号：US11389344
申请日：2006-03-24
申请人： Deepak Turaga , Michail Vlachos , Philip Yu
发明人： Deepak Turaga , Michail Vlachos , Philip Yu
IPC分类号： H04L27/00
CPC分类号： G06F17/141
摘要： Streaming environments typically dictate incomplete or approximate algorithm execution, in order to cope with sudden surges in the data rate. Such limitations are even more accentuated in mobile environments (such as sensor networks) where computational and memory resources are typically limited. Introduced herein is a novel “resource adaptive” algorithm for spectrum and periodicity estimation on a continuous stream of data. The formulation is based on the derivation of a closed-form incremental computation of the spectrum, augmented by an intelligent load-shedding scheme that can adapt to available CPU resources. Experimentation indicates that the proposed technique can be a viable and resource efficient solution for real-time spectrum estimation.
摘要翻译：流环境通常会指示不完整或近似算法执行，以应对数据速率的突然增加。在计算和存储资源通常受限制的移动环境（如传感器网络）中，这种限制更加突出。这里介绍的是一种用于连续数据流的频谱和周期估计的新型“资源自适应”算法。该公式基于频谱的闭合增量计算的推导，通过可以适应可用CPU资源的智能加载开放方案来增强。实验表明，提出的技术可以成为实时频谱估计的可行且资源有效的解决方案。

66. 发明申请

US20070214163A1 System and method for indexing a data stream 失效
标题翻译：用于索引数据流的系统和方法
公开(公告)号：US20070214163A1
公开(公告)日：2007-09-13
申请号：US11373022
申请日：2006-03-10
申请人： Gang Luo , Kun-Lung Wu , Philip Yu
发明人： Gang Luo , Kun-Lung Wu , Philip Yu
IPC分类号： G06F7/00
CPC分类号： G06F17/30442 , Y10S707/99942
摘要： There are provided methods, computer program products, and systems for indexing a data stream. A method for indexing a data stream having attribute values includes the steps of parsing the data stream, and forming an index of tuples for a subset of attribute values of the data stream. The index is configured for retrieving the top-K tuples that optimize linearly weighted sums of at least some of the attribute values in the subset.
摘要翻译：提供了用于索引数据流的方法，计算机程序产品和系统。用于索引具有属性值的数据流的方法包括解析数据流以及为数据流的属性值的子集形成元组的索引的步骤。索引被配置用于检索优化子集中的至少一些属性值的线性加权和的顶部K元组。

67. 发明申请

US20060282425A1 Method and apparatus for processing data streams 失效
标题翻译：用于处理数据流的方法和装置
公开(公告)号：US20060282425A1
公开(公告)日：2006-12-14
申请号：US11110079
申请日：2005-04-20
申请人： Charu Aggarwal , Philip Yu
发明人： Charu Aggarwal , Philip Yu
IPC分类号： G06F17/30
CPC分类号： G06F17/30592 , G06F17/30516 , G06F17/30539 , G06K9/6221
摘要： Techniques are disclosed for clustering and classifying stream data. By way of example, a technique for processing a data stream comprises the following steps/operations. A cluster structure representing one or more clusters in the data stream is maintained. A set of projected dimensions is determined for each of the one or more clusters using data points in the cluster structure. Assignments are determined for incoming data points of the data stream to the one or more clusters using distances associated with each set of projected dimensions for each of the one or more clusters. Further, the cluster structure may be used for classification of data in the data stream.
摘要翻译：公开了用于聚类和分类流数据的技术。作为示例，用于处理数据流的技术包括以下步骤/操作。保持表示数据流中的一个或多个簇的簇结构。使用集群结构中的数据点为一个或多个集群中的每一个确定一组投影尺寸。使用与每个一个或多个聚类的每一组的每个投影维度相关联的距离来确定数据流的输入数据点到一个或多个聚类的分配。此外，簇结构可以用于数据流中的数据分类。

68. 发明申请

US20060190430A1 Systems and methods for resource-adaptive workload management 失效
标题翻译：资源自适应工作负载管理的系统和方法
公开(公告)号：US20060190430A1
公开(公告)日：2006-08-24
申请号：US11063168
申请日：2005-02-22
申请人： Gang Luo , Philip Yu
发明人： Gang Luo , Philip Yu
IPC分类号： G06F17/30
CPC分类号： G06F17/30595 , G06F17/30306 , G06F17/30477 , Y10S707/954 , Y10S707/99953 , Y10S707/99956
摘要： Systems and methods are provided for resource adaptive workload management. In a method thereof, at least one execution objective is received for at least one of a plurality of queries under execution. A progress status of, and an amount of resource consumed by, each of the plurality of queries are monitored. A remaining resource requirement for each of the plurality of queries is estimated, based on the progress status of, and the amount of resource consumed by, each of the plurality of queries. Resource allocation is adjusted based on the at least one execution objective and the estimates of the remaining resource requirements.
摘要翻译：为资源自适应工作负载管理提供了系统和方法。在其方法中，为执行中的多个查询中的至少一个接收至少一个执行目标。监视多个查询中的每一个的进度状态和消耗的资源量。基于多个查询中的每个查询的消耗的进度状态和资源量来估计多个查询中的每一个的剩余资源需求。基于至少一个执行目标和剩余资源需求的估计来调整资源分配。

69. 发明申请

US20060101045A1 Methods and apparatus for interval query indexing 审中-公开
标题翻译：间隔查询索引的方法和装置
公开(公告)号：US20060101045A1
公开(公告)日：2006-05-11
申请号：US10982570
申请日：2004-11-05
申请人： Shyh-Kwei Chen , Kun-Lung Wu , Philip Yu
发明人： Shyh-Kwei Chen , Kun-Lung Wu , Philip Yu
IPC分类号： G06F17/00 , G06F7/00
CPC分类号： G06F16/2246
摘要： Interval query indexing techniques for use in accordance with data stream processing systems are disclosed. For example, in an illustrative aspect of the invention, a technique for use in processing a data stream comprises the following steps/operations. First, an attribute range of query intervals associated with the data stream is partitioned into one or more segments. Then, a set of virtual intervals is defined for each of the one or more segments. A query interval index is then built using the set of virtual intervals. The query interval index may be built by decomposing each query interval into one or more of the virtual intervals, and associating a query identifier with the decomposed virtual intervals.
摘要翻译：公开了根据数据流处理系统使用的间隔查询索引技术。例如，在本发明的说明性方面，用于处理数据流的技术包括以下步骤/操作。首先，与数据流相关联的查询间隔的属性范围被划分为一个或多个段。然后，为一个或多个段中的每一个定义一组虚拟间隔。然后使用该组虚拟间隔构建查询间隔索引。可以通过将每个查询间隔分解为虚拟间隔中的一个或多个，并将查询标识符与分解的虚拟间隔相关联来构建查询间隔索引。

70. 发明申请

US20050210027A1 Methods and apparatus for data stream clustering for abnormality monitoring 审中-公开
标题翻译：用于异常监测的数据流聚类的方法和装置
公开(公告)号：US20050210027A1
公开(公告)日：2005-09-22
申请号：US10801420
申请日：2004-03-16
申请人： Charu Aggarwal , Philip Yu
发明人： Charu Aggarwal , Philip Yu
IPC分类号： G06F17/30 , G06K9/62
CPC分类号： G06K9/6284 , Y10S707/952
摘要： Techniques for monitoring abnormalities in a data stream are provided. A plurality of objects are received from the data stream and one or more clusters are created from these objects. At least a portion of the one or more clusters have statistical data of the respective cluster. It is determined from the statistical data whether one or more abnormalities exist in the data stream.
摘要翻译：提供了用于监视数据流异常的技术。从数据流接收多个对象，并从这些对象创建一个或多个聚类。一个或多个集群的至少一部分具有相应集群的统计数据。从统计数据确定数据流中是否存在一个或多个异常。

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