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Big data measurement based on adjacent packet

A big data and quantitative technology, applied in the field of big data measurement methods and devices based on proximity grouping, can solve problems such as few sampling points, inability to handle data volume, difficult processing, etc.

Inactive Publication Date: 2015-11-11
成都博元时代软件有限公司
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  • Description
  • Claims
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Problems solved by technology

It is well known to those skilled in the art that if low-dimensional data is used, the required sampling points will be relatively small; if the data is multi-dimensional or even high-dimensional, the required sampling points will increase exponentially surprisingly, while in reality For multi-dimensional problems, it is often impossible to obtain so many sample points (even if obtained, it cannot handle such a huge amount of data), so it is extremely difficult to deal with this problem

Method used

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  • Big data measurement based on adjacent packet

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Embodiment Construction

[0014] In the following description, reference is made to the accompanying drawings, which show several specific embodiments by way of illustration. It will be understood that other embodiments can be conceived and can be made without departing from the scope or spirit of the present disclosure. Therefore, the following detailed description should not be considered in a limiting sense.

[0015] According to an embodiment of the present invention, figure 1 A flow chart illustrating a proximity grouping-based big data measurement method is applicable and suitable for a proximity grouping-based big data architecture.

[0016] First, in step S1, the weight of elements in the adjacent group is determined, and the weight is either based on the position of the element in the adjacent group, or based on the distance between an element and other data points. An element Xj is a neighbor of all or some elements in a neighbor group of other elements. Preferably, the weight associated w...

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Abstract

The present invention provides a big data measurement method based on an adjacent packet and an apparatus for performing the steps of the method. The method comprises the steps of: determining a weight of each element in the adjacent packet; relative to the element Xj, obtaining the number of other elements whose adjacent degree with the element Xj is L in the adjacent packet; relative to the element Xj, obtaining the number of the elements whose adjacent degree with the element Xj is L in an element packet that is classified as d; if the element Xj appears in an adjacent set, obtaining a probability of the element Xj that is classified as d; obtaining the other probability related to the element Xj that is classified as d; and obtaining a relationship degree Rd (Xj) related to the element Xj in the class d. By means of the measurement method and apparatus provided by the present invention, a measurement mode is improved and optimized to make significant measurement, which lays a basis for further big data processing.

Description

technical field [0001] The present invention relates to the field of big data information processing, and more specifically, to a method and device for measuring big data based on adjacent grouping. Background technique [0002] With the continuous improvement of social industrialization and informatization, data has replaced computing as the center of information computing, and cloud computing and big data are becoming a trend and trend. Including storage capacity, availability, I / O performance, data security, scalability and many other aspects. Big data is very large and complex datasets. Big data has 4V: Volume (a large amount), the amount of data continues to increase rapidly; Velocity (high speed), data I / O speed is faster; Variety (variety), data types and sources are diversified; Value (value), it exists in all aspects available value. At the same time, in the mining application of big data, most of the data of interest is often complex, and due to the complexity o...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 杨立波
Owner 成都博元时代软件有限公司
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