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A method and device for mining frequent episodes of multi-source data streams

A technology of frequent plots and data streams, applied in the fields of electronic digital data processing, digital data information retrieval, special data processing applications, etc., can solve problems such as mining, and achieve the effect of reducing complexity, plot redundancy, and storage overhead.

Active Publication Date: 2022-03-11
NORTHWESTERN POLYTECHNICAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present invention provides a method and device for mining frequent episodes of multi-source data streams, which are used to solve the problem that the mining object of the existing data stream mining technology is a single data stream, which cannot be mined for multiple levels, multiple angles, and multiple directions.

Method used

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  • A method and device for mining frequent episodes of multi-source data streams
  • A method and device for mining frequent episodes of multi-source data streams
  • A method and device for mining frequent episodes of multi-source data streams

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Embodiment 1

[0105] Figure 4 A schematic diagram of a data flow structure with a "sequential relationship" provided by Embodiment 1 of the present invention; Figure 5 Provide and Figure 4 Schematic diagram of the corresponding data grid structure.

[0106] Such as Figure 4 As shown, there is W in the figure (1) , W (2) Two data streams, where W (1) :ADCADCBC...,W (2) :BECABEAA…. W (1) , W (2) The sequence relationship of the data items included in the two data streams is as follows: Figure 4 shown. Figure 5 In , use '·' to indicate that there is no sequence relationship between the corresponding two events, and use '×' to indicate that there is a sequence relationship between the corresponding two events.

[0107] For data flow W (1) and W (2) , can be based on Figure 5 Perform frequent episode mining. Specifically include:

[0108] Step 501, traverse the entire data grid to find the first multi-sequence data grid M 31 ;

[0109] Step 502, determine the composition...

Embodiment 2

[0118] Image 6 It is a schematic diagram of a method for mining frequent episodes of multi-source data streams provided by Embodiment 2 of the present invention, as shown in Image 6 As shown, the method includes the following steps:

[0119] Step 601, combining two sets of data streams without sequence relationship into a data grid;

[0120] Step 602, traversing the data grids without sequence relationship, if it is confirmed that the data grid contains single-sequence data grids, then perform step 603, if it is confirmed that the data grid contains multi-sequence data grids, then perform step 604;

[0121]Step 603, since the single-sequence data grid can generate a unique sequence, confirm the first data item or the second data item that constitutes the first single-sequence data grid from the data flow without sequence relationship, according to the first data item or the second data item Two data items, directly generate a sequence of single-sequence data grids;

[012...

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Abstract

The invention discloses a method and device for mining frequent episodes of multi-source data streams, and relates to the technical field of data mining. The mining object used to solve the existing data stream mining technology is a single data stream, and there is a problem that mining cannot be carried out for multi-level, multi-angle and multi-directional. The method includes: starting from an initial point position of a data grid, traversing a data stream including data points without a sequence relationship in the data grid, and according to the characteristics of the data streams corresponding to different processes occurring at intervals, traversing the data streams without a sequence relationship Streams are identified as sequences of data lattices; mixed frequent episodes in the sequences of data lattices are identified by frequent episode mining methods.

Description

technical field [0001] The present invention relates to the technical field of data mining, and more specifically relates to a method and device for mining frequent plots of multi-source data streams. Background technique [0002] At present, data mining has been widely used in intelligent transportation systems. It is established by effectively integrating advanced information technology, data communication transmission technology, electronic sensing technology, control technology and computer technology into the entire ground traffic management system. It is a real-time, accurate and efficient comprehensive transportation management system that works in a wide range and in all directions. The application of frequent episode mining of multi-source data streams in the flow control of intelligent traffic sections is mainly based on the passing road information data collected by traffic sensors on different vehicles, combined with the frequent episode mining method of multi-so...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2455G06F16/2458
Inventor 尤涛杜承烈陈进朝李亚敏李宇博
Owner NORTHWESTERN POLYTECHNICAL UNIV
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