Method for extracting longest common substring of time series data

A technology of the longest common substring and time series, which is applied in the fields of electrical digital data processing, special data processing applications, digital data information retrieval, etc., and can solve problems such as lack of research papers

Pending Publication Date: 2019-09-13
SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology allows us to easily find long periods or parts that have been lost during certain types of analysis such as power system monitoring.

Problems solved by technology

This patented technical solution describes how long common words like phone numbers or email addresses may appear similar when compared across multiple documents with each other due to differences caused by factors like communication speed. Existing techniques use string analysis to calculate these terms but they cannot handle any changes that might occur during this process. Therefore there needs an effective way to find specific patterns within longer sequences called frequent repetitions found near them.

Method used

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  • Method for extracting longest common substring of time series data
  • Method for extracting longest common substring of time series data
  • Method for extracting longest common substring of time series data

Examples

Experimental program
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Embodiment 1

[0067] This embodiment takes the pulse time series as an example.

[0068] Step 1, read the pulse time series to be compared; the pulse time series to be compared uses two types of data, as shown in Table 1.

[0069] Table 1:

[0070]

[0071] According to Table 1, among the two types of pulse time series used in this embodiment, one is two groups of pulse time series to be compared without loss; the other is two groups of pulse time series to be compared with partial loss .

[0072] Step 2. Select the time characteristic parameters of the pulse time series as calculation parameters, and perform differential transformation, quantization processing, and symbolization processing on the pulse time series to obtain a symbolic sequence; The symbolized sequence is shown in Table 2.

[0073] Table 2:

[0074]

[0075]

[0076] Step 3, establishing an equivalent character list of the pulse time series according to the symbolized sequence;

[0077] Considering that the maxim

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Abstract

The invention discloses a method for extracting a longest common substring of time series data. The method comprises the following steps: step 1, reading to-be-compared time series data; step 2, selecting a time characteristic parameter of the time sequence data as a calculation parameter, and performing differential transformation, quantitative processing and symbolization processing on the timesequence data to obtain a symbolized sequence; step 3, establishing an equivalent character table of time sequence data according to the symbolized sequence; step 4, according to the equivalent character table, searching and storing a common substring of the time sequence data by adopting a dynamic sliding window mode; and step 5, extracting the longest common substring by judging the length of the common substring. According to the longest common substring extraction method for the time sequence data, the longest common substring of the time sequence data can be quickly extracted, and the longest common substring is also effective under the condition that the data part of the time sequence is lost.

Description

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Claims

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Application Information

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Owner SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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