Data value degree calculation method based on analytic hierarchy process

A technique of analytic hierarchy process and calculation method, which is applied in the direction of calculation, electrical digital data processing, special data processing applications, etc., and can solve problems such as low accuracy and low storage efficiency

Inactive Publication Date: 2017-01-25
DALIAN UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0011] In order to overcome the above problems of low storage efficiency and low accuracy, the present invention proposes a data value calculation method based on the analytic hierarchy process. This characteristic value n

Method used

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  • Data value degree calculation method based on analytic hierarchy process
  • Data value degree calculation method based on analytic hierarchy process
  • Data value degree calculation method based on analytic hierarchy process

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0053] This embodiment provides a data value calculation method based on the analytic hierarchy process. The calculation formula of the value λ of data x is as follows:

[0054] λ ( x ) = a 1 1 S + a 2 T + a 3 F + a 4 C + a 5 D + a 6 V

[0055] ①S represents the data size; for a storage system that has reached the PB level, it is impossible to use a high-performance disk array with high cost. Therefore, for a storage system built with hybrid disks, small and hot files are more suitable for storage in In high-performance disk arrays with high performance and limited capacity, the unit is megabytes;

[0056] ②T represents the access time interval; the newly created or recentl...

Embodiment 2

[0070] As a supplement to Example 1, the calculation method of the expected value V of the data is:

[0071] Step 1: Assume that users who have accessed data x are represented by G, and other users are represented by H, then:

[0072] G={g 1 , g 2 ,...,g n}

[0073] H={h 1 ,h 2 ,...,h m}

[0074] Said n and m are the total number of users;

[0075] Step 2: Calculate the similarity of G and H elements to obtain a similarity matrix:

[0076] S i m ( G i , H j ) = S 11 S 12 ... S 1 m S 21...

Embodiment 3

[0084] As a further supplement to Embodiment 1 or 2, the constructed judgment matrix P is as follows:

[0085] P = 1 3 3 1 3 1 5 1 3 1 3 1 1 1 1 15 1 9 1 3 1 1 1 ...

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Abstract

The invention provides a data value degree calculation method based on an analytic hierarchy process. A calculation formula of a value degree lambda of a data x is as follows: lambda(x)=a1*(1/S)+a2T+a3F+a4C+a5D+a6V, wherein S represents data size; T represents an access time interval; the longer the unused time of the data after access is, the lower the importance and the value degree of the data are, and the probability that the data is accessed again is correspondingly reduced; F represents read-write frequency of the data; the value of the data with high read-write frequency is higher; C represents the quantity of users access; the larger the number of users accessing the data is, the higher the value of the data is; D represents content of a file; V represents a prospective value of the data; the value is obtained through calculation of similarity of the users; a1, a2, a3, a4, a5 and a6 are weighting coefficients of itemized attributes of a computer characteristic value lambda respectively. According to the characteristic value, the data size, the access time, the file content, the read-write frequency of the data and the access quantity are taken into consideration, and meanwhile, the importance of the data and the access probability of the data in a future period of time are also taken into consideration.

Description

technical field [0001] The invention belongs to the field of decision-making value evaluation, in particular to a data value degree calculation method based on the analytic hierarchy process. Background technique [0002] The era of big data has arrived, data is growing rapidly, and the amount of data has become huge, reaching EB (10 12 GB) level, data types are gradually increasing, of which unstructured data, such as network logs, audio and video, pictures, geographical location information, etc. exceed 80%, the value density of data is quite low, and it needs to be extracted through data filtering and data analysis out its value. In response to the storage requirements for a large amount of unstructured data, traditional storage methods cannot meet the increasing data storage requirements. Hierarchical storage management technology provides ideas for solving this problem. [0003] The hierarchical storage structure of the storage system is a pyramidal structure composed...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 邱少明张冬杜秀丽
Owner DALIAN UNIVERSITY
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