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A method for extracting dominating set information of time sequence data

A time-series data and information extraction technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problem that time-series data extraction methods are difficult to meet the needs of large-scale storage and high real-time information extraction

Active Publication Date: 2018-12-18
HEILONGJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing time series data extraction method is difficult to meet the large-scale storage and high real-time information extraction requirements. The invention provides a time series data dominance set information extraction method

Method used

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  • A method for extracting dominating set information of time sequence data
  • A method for extracting dominating set information of time sequence data
  • A method for extracting dominating set information of time sequence data

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specific Embodiment approach 1

[0029] Specific implementation mode one: see figure 2 Describe this embodiment, the time series data dominant set information extraction method described in this embodiment, the method includes the following process:

[0030] Firstly, users with dominance ability are selected in massive user big data, and other users are associated users of users with dominance ability, and a conversion function I is established from dominance users to associated users; among them, dominance users are users with dominance ability;

[0031] Then, in the face of continuously collected user time series data, store the dominant user data as small data, and dynamically update the transformation function I;

[0032] Finally, through the dominant user data and the updated transformation function I, the data information of associated users that meets user requirements is extracted, so as to extract the big data information represented by associated user data from the small data represented by dominan...

specific Embodiment approach 2

[0037] Specific implementation mode two: see figure 2 This embodiment is described. The difference between this embodiment and the time-series data dominance set information extraction method described in the first specific embodiment is that the specific process of selecting a user with dominance ability in a large amount of user big data is to pass between time-series data vectors. To realize the selection of users with dominance ability.

specific Embodiment approach 3

[0038] Specific implementation mode three: see figure 2 Describe this embodiment. The difference between this embodiment and the time-series data dominating set information extraction method described in Embodiment 1 is that the conversion function I from the dominating user to the associated user is:

[0039] I:δ=Aρ+B;

[0040] Among them, ρ=(u,λ), and ρ is the order vector of the dominant user;

[0041] δ=(u, s), and δ is the associated user sequence even vector;

[0042] A is the coefficient matrix;

[0043] B is the bias matrix;

[0044] u is the public user sample vector;

[0045] λ is the dominant user sample vector;

[0046] s is the associated user sample vector.

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Abstract

A method for extract dominating set information of time sequence data belongs to that information extraction field of Internet and Internet of things. The method solves the problem that the existing temporal data extraction methods cannot meet the needs of large-scale storage and high real-time information extraction. At first, the user with dominating ability is selected from the mass user big data, and the other users are taken as the associate users of the users with dominating ability, and the transformation function I from the dominating user to the associated user is established; then, in the face of continuously collected user timing data, the dominant user data is stored as small data, and the transform function I is updated dynamically. By dominating the user data and the updatedtransform function I, the data information of the associated user satisfying the user requirements is extracted, so that the big data information represented by the associated user data is extracted from the small data represented by the dominating user data. Mainly used in the Internet, the Internet of things and other information extraction related fields.

Description

technical field [0001] The invention belongs to the field of information extraction from the Internet and the Internet of Things. Background technique [0002] At present, time-series data processing based on large-scale real-time data has gradually become a key issue in the field of information technology such as the Internet and the Internet of Things. The processing process is time-series data collection, storage, and information extraction. For details, see figure 1 . Facing the continuous arrival of massive time-series data, the data processing system must quickly respond to it and extract information in time to ensure the quality of information service. [0003] Time series data information extraction involves meteorology, environmental protection monitoring, information collection of power supply, water supply, and heating systems, transaction information analysis systems for stock and futures markets, and industrial process detection application systems and many oth...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 伍一
Owner HEILONGJIANG UNIV
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