公开(公告)号：US07437397B1

公开(公告)日：2008-10-14

申请号：US10822316

申请日：2004-04-12

申请人： Nikolaos Koudas ,  Sudipto Guha

发明人： Nikolaos Koudas ,  Sudipto Guha

IPC分类号： G06F17/15

CPC分类号： G06K9/00536

摘要： Certain exemplary embodiments provide a method comprising: automatically: receiving a plurality of elements for each of a plurality of continuous data streams; treating the plurality of elements as a first data stream matrix that defines a first dimensionality; reducing the first dimensionality of the first data stream matrix to obtain a second data stream matrix; computing a singular value decomposition of the second data stream matrix; and based on the singular value decomposition of the second data stream matrix, quantifying approximate linear correlations between the plurality of elements.

摘要翻译： 某些示例性实施例提供了一种方法，包括：自动地：接收多个连续数据流中的每一个的多个元素; 将所述多个元素作为限定第一维度的第一数据流矩阵; 减少第一数据流矩阵的第一维度以获得第二数据流矩阵; 计算第二数据流矩阵的奇异值分解; 并且基于第二数据流矩阵的奇异值分解，量化多个元素之间的近似线性相关性。

公开(公告)号：US20100057805A1

公开(公告)日：2010-03-04

申请号：US12615805

申请日：2009-11-10

申请人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

发明人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

IPC分类号： G06F17/30

CPC分类号： G06F17/30548 ,  G06F2216/03 ,  Y10S707/99936 ,  Y10S707/99943

摘要： A system, method and computer-readable medium are disclosed for identifying representative data using sketches. The method embodiment comprises generating a plurality of vectors from a data set, modifying each of the vectors of the plurality of vectors and selecting one of the plurality of generated vectors according to a comparison of a summed distance between a modified vector associated with the selected generated vector and remaining modified vectors. Modifying the generated vectors may involve reduced each generated vector to a lower dimensional vector. The summed distance then represents a summed distance between the lower dimensional vector and remaining lower dimensional vectors.

摘要翻译： 公开了一种使用草图识别代表性数据的系统，方法和计算机可读介质。 方法实施例包括从数据集生成多个向量，修改多个向量中的每一个向量，并且根据与所选生成的所生成的向量相关联的修改向量之间的总和距离的比较来选择多个生成向量中的一个 载体和剩余的修饰载体。 修改所生成的向量可以将每个生成的向量减少到较低维度向量。 然后，求和距离表示较低维度向量和剩余的较低维度向量之间的总和距离。

公开(公告)号：US20080275908A1

公开(公告)日：2008-11-06

申请号：US12171911

申请日：2008-07-11

申请人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

发明人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

IPC分类号： G06F17/30

CPC分类号： G06F17/30548 ,  G06F2216/03 ,  Y10S707/99936 ,  Y10S707/99943

摘要： A system, method and computer-readable medium are disclosed for identifying representative data using sketches. The method embodiment comprises generating a plurality of vectors from a data set, modifying each of the vectors of the plurality of vectors and selecting one of the plurality of generated vectors according to a comparison of a summed distance between a modified vector associated with the selected generated vector and remaining modified vectors. Modifying the generated vectors may involve reduced each generated vector to a lower dimensional vector. The summed distance then represents a summed distance between the lower dimensional vector and remaining lower dimensional vectors.

摘要翻译： 公开了一种使用草图识别代表性数据的系统，方法和计算机可读介质。 方法实施例包括从数据集生成多个向量，修改多个向量中的每一个向量，并且根据与所选生成的所生成的向量相关联的修改向量之间的总和距离的比较来选择多个生成向量中的一个 载体和剩余的修饰载体。 修改所生成的向量可以将每个生成的向量减少到较低维度向量。 然后，求和距离表示较低维度向量和剩余的较低维度向量之间的总和距离。

公开(公告)号：US06931400B1

公开(公告)日：2005-08-16

申请号：US10083812

申请日：2002-02-27

申请人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

发明人： Piotr Indyk ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

IPC分类号： G06F17/30

CPC分类号： G06F17/30548 ,  G06F2216/03 ,  Y10S707/99936 ,  Y10S707/99943

摘要： A method and system for identifying representative data trends using sketches. A sketch is a lower dimensional vector used to represent higher dimensional data. The properties of sketches include data dimensionality reduction, sketches synthesized from other sketches, and the distance between sketches comparable to the distance between the data the sketches represent. Exemplary embodiments include identifying relaxed periods and average trends.

摘要翻译： 一种使用草图识别代表性数据趋势的方法和系统。 草图是用于表示较高维数据的较低维度向量。 草图的属性包括数据维度降低，从其他草图合成的草图以及草图之间的距离与草图表示的数据之间的距离相当。 示例性实施例包括识别放宽时段和平均趋势。

公开(公告)号：US06738762B1

公开(公告)日：2004-05-18

申请号：US09994266

申请日：2001-11-26

申请人： Zhiyuan Chen ,  Philip Russell Korn ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

发明人： Zhiyuan Chen ,  Philip Russell Korn ,  Nikolaos Koudas ,  Shanmugavelayutham Muthukrishnan

IPC分类号： G06F1730

CPC分类号： G06F17/30592 ,  G06F17/30469 ,  Y10S707/957 ,  Y10S707/99933 ,  Y10S707/99942 ,  Y10S707/99943

摘要： An approach for multidimensional substring selectivity estimation utilizes set hashing to generate cross-counts as needed, instead of storing cross-counts for the most frequently co-occurring substrings. Set hashing is a Monte Carlo technique that is used to succinctly represent the set of tuples containing a given substring. Then, any combination of set hashes will yield a cross-count when intersected. Thus, the set hashing technique is useful in three-, four- and other multidimensional situations, since only an intersection function is required.

摘要翻译： 用于多维子串选择性估计的方法利用集合散列来根据需要产生交叉计数，而不是存储最频繁共同子串的交叉计数。 设置散列是一种蒙特卡罗技术，用于简洁地表示包含给定子字符串的元组集合。 然后，任何组合哈希值将在交叉时产生交叉计数。 因此，集合散列技术在三维，四维和其他多维情况下是有用的，因为只需要一个交集函数。