公开(公告)号：US07684963B2

公开(公告)日：2010-03-23

申请号：US11092495

申请日：2005-03-29

Applicant: Charu Aggarwal

Inventor： Charu Aggarwal

IPC: G06F7/60 ,  G06K9/62

CPC classification number: G06F17/30705

Abstract: Systems and methods for providing density-based traffic generation. Data are clustered to create partitions, and transforms of clustered data are constructed in a transformed space. Data points are generated via employing grid discretization in the transformed space, and density estimates of the generated data points are employed to generate synthetic pseudo-points.

Abstract translation: 提供基于密度的流量生成的系统和方法。 数据被聚集以创建分区，并且在变换的空间中构建聚类数据的变换。 通过在变换空间中采用网格离散化来生成数据点，并且采用生成的数据点的密度估计来生成合成伪点。

公开(公告)号：US20090049069A1

公开(公告)日：2009-02-19

申请号：US11836171

申请日：2007-08-09

Applicant: Charu Aggarwal ,  Philip S. Yu

Inventor： Charu Aggarwal ,  Philip S. Yu

IPC: G06F17/30

CPC classification number: H04L63/0407 ,  G06F21/6254 ,  Y10S707/99942 ,  Y10S707/99943

Abstract: Privacy in data mining of sparse high dimensional data records is preserved by transforming the data records into anonymized data records. This transformation involves creating a sketch-based private representation of each data record, each data record containing only a small number of non-zero attribute value in relation to the high dimensionality of the data records.

Abstract translation: 通过将数据记录转换为匿名数据记录来保留稀疏高维数据记录的数据挖掘隐私。 该变换涉及创建每个数据记录的基于草图的私有表示，每个数据记录仅包含相对于数据记录的高维数的少量非零属性值。

公开(公告)号：US20080040346A1

公开(公告)日：2008-02-14

申请号：US11872424

申请日：2007-10-15

Applicant: Charu Aggarwal ,  Philip Shi-Lung Yu

Inventor： Charu Aggarwal ,  Philip Shi-Lung Yu

IPC: G06F17/30

CPC classification number: G06F17/30592 ,  Y10S707/957 ,  Y10S707/99931 ,  Y10S707/99942 ,  Y10S707/99943

Abstract: Methods and apparatus for generating at least one output data set from at least one input data set for use in association with a data mining process are provided. First, data statistics are constructed from the at least one input data set. Then, an output data set is generated from the data statistics. The output data set differs from the input data set but maintains one or more correlations from within the input data set. The correlations may be the inherent correlations between different dimensions of a multidimensional input data set. A significant amount of information from the input data set may be hidden so that the privacy level of the data mining process may be increased.

Abstract translation: 提供了用于从与数据挖掘过程相关联使用的至少一个输入数据集生成至少一个输出数据集的方法和装置。 首先，从至少一个输入数据集构建数据统计。 然后，从数据统计生成输出数据集。 输出数据集与输入数据集不同，但保持与输入数据集内的一个或多个相关。 相关性可以是多维输入数据集的不同维度之间的固有相关性。 可以隐藏来自输入数据集的大量信息，从而可以增加数据挖掘过程的隐私级别。

公开(公告)号：US20070226212A1

公开(公告)日：2007-09-27

申请号：US11753232

申请日：2007-05-24

Applicant: Charu Aggarwal ,  Philip Yu

Inventor： Charu Aggarwal ,  Philip Yu

IPC: G06F17/30

CPC classification number: G06K9/6284 ,  Y10S707/952

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20060064438A1

公开(公告)日：2006-03-23

申请号：US10943329

申请日：2004-09-17

Applicant: Charu Aggarwal

Inventor： Charu Aggarwal

IPC: G06F17/30

CPC classification number: G06N20/00

Abstract: A technique for monitoring a primary data stream comprising one or more secondary data streams for abnormalities is provided. A deviation value is determined for each of the one or more secondary data streams. The determined deviation values of the one or more secondary data streams are combined to form a combined deviation value. The combined deviation value is used to generate an abnormality signal.

Abstract translation: 提供了一种用于监视包括用于异常的一个或多个次要数据流的主数据流的技术。 确定一个或多个次要数据流中的每一个的偏差值。 将一个或多个次要数据流的确定的偏差值组合以形成组合偏差值。 组合偏差值用于产生异常信号。

公开(公告)号：US20050038769A1

公开(公告)日：2005-02-17

申请号：US10641951

申请日：2003-08-14

Applicant: Charu Aggarwal ,  Philip Yu

Inventor： Charu Aggarwal ,  Philip Yu

IPC: G06F17/30 ,  G06F7/00

CPC classification number: G06F17/30516 ,  G06F17/30598 ,  Y10S707/99931 ,  Y10S707/99943

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US08914371B2

公开(公告)日：2014-12-16

申请号：US13324513

申请日：2011-12-13

Applicant: Charu Aggarwal ,  Karthik Subbian

Inventor： Charu Aggarwal ,  Karthik Subbian

IPC: G06F7/00

CPC classification number: G06F17/30516 ,  G06F17/3071 ,  H04L51/32

Abstract: A method and system for detecting an event from a social stream. The method includes the steps of: receiving a social stream from a social network, where the social stream includes at least one object and the object includes a text, sender information of the text, and recipient information of the text; assigning said object to a cluster based on a similarity value between the object and the clusters; monitoring changes in at least one of the clusters; and triggering an alarm when the changes in at least one of the clusters exceed a first threshold value, where at least one of the steps is carried out using a computer device.

Abstract translation: 一种用于从社交流中检测事件的方法和系统。 该方法包括以下步骤：从社交网络接收社交流，其中社交流包括至少一个对象，并且对象包括文本，文本的发送者信息和文本的接收者信息; 基于对象和群集之间的相似度值将所述对象分配给群集; 监视至少一个集群的变化; 并且当至少一个所述簇中的变化超过第一阈值时触发报警，其中使用计算机设备执行至少一个所述步骤。

公开(公告)号：US08655805B2

公开(公告)日：2014-02-18

申请号：US12871168

申请日：2010-08-30

Applicant: Charu Aggarwal

Inventor： Charu Aggarwal

IPC: G06F15/18

CPC classification number: G06N99/005

Abstract: A method for classifying objects in a graph data stream, including receiving a training stream of graph data, the training stream including a plurality of objects along with class labels that are associated with each of the objects, first determining discriminating sets of edges in the training stream for the class labels, wherein a discriminating set of edges is one that is indicative of the object that contains these edges having a given class label, receiving an incoming data stream of the graph data, wherein class labels have not yet been assigned to objects in the incoming data stream, second determining, based on the discriminating sets of edges, class labels that are associated with the objects in the incoming data stream; and outputting to an information repository object class label pairs based on the second determining.

Abstract translation: 一种用于对图形数据流中的对象进行分类的方法，包括接收图形数据的训练流，训练流包括多个对象以及与每个对象相关联的类标签，首先确定训练中的边缘识别集合 用于类标签的流，其中，鉴别集合的边是指示包含具有给定类标签的这些边的对象，接收图数据的输入数据流，其中类标签尚未被分配给对象 在输入数据流中，基于所识别的边缘集合，第二确定与输入数据流中的对象相关联的类标签; 以及基于所述第二确定将信息输出到信息库对象类标签对。

公开(公告)号：US08375061B2

公开(公告)日：2013-02-12

申请号：US12796266

申请日：2010-06-08

Applicant: Charu Aggarwal

Inventor： Charu Aggarwal

IPC: G06F17/30

CPC classification number: G06F17/30619

Abstract: In a method for representing a text document with a graphical model, a document including a plurality of ordered words is received and a graph data structure for the document is created. The graph data structure includes a plurality of nodes and edges, with each node representing a distinct word in the document and each edge identifying a number of times two nodes occur within a predetermined distance from each other. The graph data structure is stored in an information repository.

Abstract translation: 在用图形模型表示文本文档的方法中，接收包括多个有序字的文档，并创建文档的图形数据结构。 图形数据结构包括多个节点和边缘，其中每个节点表示文档中的不同字，每个边缘标识两个节点彼此之间预定距离内发生的次数。 图形数据结构存储在信息库中。

公开(公告)号：US20070288465A1

公开(公告)日：2007-12-13

申请号：US11243727

申请日：2005-10-05

Applicant: Charu Aggarwal ,  Philip Yu

Inventor： Charu Aggarwal ,  Philip Yu

IPC: G06F7/00

CPC classification number: G06Q10/00

Abstract: Improved techniques are disclosed for detecting patterns of interaction among a set of entities and analyzing community evolution in a stream environment. By way of example, a technique for processing data from a data stream includes the following steps/operations. A data point of the data stream representing an interaction event is obtained. An interaction graph is updated on-line based on the data point representing the interaction event. The updated interaction graph is stored in a nonvolatile memory. An interaction evolution is determined off-line from the updated interaction graph stored in the nonvolatile memory.

Abstract translation: 公开了用于检测一组实体之间的交互模式并分析流环境中的社区进化的改进的技术。 作为示例，用于从数据流处理数据的技术包括以下步骤/操作。 获得表示交互事件的数据流的数据点。 基于表示交互事件的数据点，在线更新交互图。 更新的交互图存储在非易失性存储器中。 从存储在非易失性存储器中的更新的交互图中离线确定交互演进。