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Class periodic rule mining method based on temporal data system

A technology of temporal data and rules, applied in data mining, database indexing, electronic digital data processing, etc.

Inactive Publication Date: 2019-08-23
曲逸文
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Problems solved by technology

[0002] The current data rule mining technology is mainly concentrated in the traditional trend analysis and correlation analysis field, which is used to reveal the development trend and causal knowledge of the target data system; its analysis of the periodic law of events is mainly for some mathematically rigorous Periodic rules are mined, and there is a lack of means for real-time analysis of periodic rules without mathematical meaning

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  • Class periodic rule mining method based on temporal data system
  • Class periodic rule mining method based on temporal data system
  • Class periodic rule mining method based on temporal data system

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Embodiment Construction

[0061] refer to figure 1 A description model of the temporal data system under the structure of the periodic rule mining method based on the temporal data system of the present invention is established.

[0062] A. Perform temporal processing on the attributes of interest in the temporal data system, and construct a sequence of observation points for time-series feature data and attributes of interest;

[0063] The model description of the temporal data system is as follows: record the time interval of the objective temporal system as T={t 1 ,t 2 ...t n}; the attention attribute is denoted as F={F 1 , F 2 …F m}, m is the dimension of the concerned attribute; the feature value of the concerned attribute is recorded as f={f 1 ,f 2 … f p}, p is the dimension of the feature; the time interval from recording to updating the feature value of the attribute concerned is recorded as the life cycle T of the attribute concerned l =[T b , T e ], the characteristic value of the ...

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Abstract

The invention discloses a class periodic rule mining method based on a tense data system, which is used for discovering class periodic rules among tense related attributes without obvious periodic characteristics. The method comprises the following steps: carrying out tense processing on attention attributes in a tense data system, and constructing time sequence characteristic data; performing inertia calculation on the time sequence characteristic data to obtain an inertia trend sequence of the attention attribute; on the basis of the inertia trend sequence, calculating peak-valley chain characteristics of the concerned attributes; constructing a peak-valley statistical index sequence of the attention attributes; and obtaining a class periodic rule of the data system through span discretedifference calculation. According to the invention, association rule calculation can be carried out on the periodic phenomenon without mathematical significance; the flexibility of time periods and the interference of noise data are overcome, class periodic rules are mined, the method has good timeliness and reliability, rule mining can be carried out on big data of emergencies and unpredictableevents, people are guided to tend to avoid harm, and the method has good practical benefits.

Description

technical field [0001] The invention relates to a method for mining periodicity-like rules based on a temporal data system, and belongs to the fields of computer big data and cloud computing. Background technique [0002] The current data rule mining technology is mainly concentrated in the traditional trend analysis and correlation analysis field, which is used to reveal the development trend and causal knowledge of the target data system; its analysis of the periodic law of events is mainly for some mathematically rigorous Periodic rules are mined, and there is a lack of means for real-time analysis of periodic rules without mathematical meaning. Contents of the invention [0003] In order to solve the above problems, the present invention provides a method for real-time mining based on the periodicity-like rules of the temporal data system to discover the periodicity-like rules between temporal related attributes without obvious periodicity. [0004] Technical scheme o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/22
CPCG06F2216/03G06F16/2228G06F16/2474G06F16/2465
Inventor 曲逸文衣学武
Owner 曲逸文
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