Comprehensive Situation Quantitative Processing Method for Big Data Analysis

A processing method and big data technology, applied in the field of computer networks, can solve problems such as the failure of quantitative processing methods, failure to consider correlations, accumulation of entity weights, etc., and achieve effective and accurate results of quantitative processing

Active Publication Date: 2018-06-12
王娟磊
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  • Application Information

AI Technical Summary

Problems solved by technology

However, this method does not consider the relationship between entities, which can easily cause the phenomenon of entity weights to accumulate upwards, which in turn leads to the failure of quantitative processing methods
[0004] The iterative quantitative processing method with the PageRank algorithm as the core and its variant processing methods are all search algorithms with the goal of searching in essence, and the pathological entity repair mechanism adopted is essentially a "problem supervision", while It is not "full-staff supervision". Therefore, this method is likely to cause the weight of peripheral environmental entities and their direct predecessor entities to be too large in the entire quantitative processing system, while the weight of direct successor entities is too small, which will cause the quantitative processing method to fail

Method used

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  • Comprehensive Situation Quantitative Processing Method for Big Data Analysis
  • Comprehensive Situation Quantitative Processing Method for Big Data Analysis
  • Comprehensive Situation Quantitative Processing Method for Big Data Analysis

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Embodiment

[0027] Such as figure 1 As shown, the comprehensive situation quantitative processing method for big data analysis in this embodiment includes the following steps:

[0028] The first step, system initialization: form the entity attribute set e with all entity attributes of the entity in the target scene, and form the entity attribute value vector w(e) with all entity attribute values n×1 =(w(e 1 ),w(e 2 ),...,w(e n )) T , n is the number of entity attributes; set the iteration threshold ξ at the same time; go to the second step;

[0029] The specific process is: set entity attribute set e=[e 1 ,e 2 ,...,e n ], entity attribute value vector w(e) n×1 =(w(e 1 ),w(e 2 ),...,w(e n )) T , iteration threshold ξ, where n is the number of entity attributes, that is, n=|e|, w(e 1 ),w(e 2 ),...,w(e n ) are entity attributes e 1 ,e 2 ,...,e n Entity property value for ; go to step two.

[0030] The second step is to construct the matrix: set the transferable entity attr...

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Abstract

The invention relates to a comprehensive tendency quantitative treating method for big data analysis. The method comprises the steps of 1, initializing a system; 2, constructing a matrix; 3, modifying the matrix; 4, converting the matrix; 5, iteratively processing; 6, normalizing. The method can overcome the shortages in the existing comprehensive tendency quantitative treating method and can improve the evaluation accuracy.

Description

technical field [0001] The invention relates to a comprehensive situation quantitative processing method for big data analysis, the core of which is the improvement of the deep analysis mechanism of big data, belonging to the technical field of computer network. Background technique [0002] As far as the applicant knows, in the current big data analysis, the core ideas of the quantitative processing method for the comprehensive situation of the target scene mainly include: the simple quantitative processing method with the statistical function as the core, the iterative quantitative processing method with the PageRank algorithm as the core, and Its variant processing method. [0003] In the actual quantitative processing process, the simple quantitative processing method with the statistical function as the core takes the entity attribute value list of each entity in the target scene (that is, the target large data set) as the object within a certain statistical period, and...

Claims

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): G06F17/30
Inventor王娟磊
Owner王娟磊