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Method for mining frequency episode from event sequence by using same node chains and Hash chains

A technology of event sequences and plots, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effect of improving time and space performance

Inactive Publication Date: 2011-05-25
NORTHEASTERN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems existing in the existing mining methods, the present invention provides a method for mining frequent episodes of event sequences based on the same node chain and hash chain for the smallest frequent episodes on the event sequence

Method used

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  • Method for mining frequency episode from event sequence by using same node chains and Hash chains
  • Method for mining frequency episode from event sequence by using same node chains and Hash chains
  • Method for mining frequency episode from event sequence by using same node chains and Hash chains

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Embodiment Construction

[0038] The present invention will be further described in detail below with reference to the drawings and examples.

[0039] Such as figure 1 As shown, the steps of the method of the present invention include:

[0040] (1) Initialize the relevant data structure. include:

[0041] ① Encode the event types contained in the event sequence in the order of increasing natural numbers. If the event type e is encoded as m, it will be represented as e in the following description m , Where 1≤m≤n, n is the number of event types in the event sequence;

[0042] ②Initialize the count and time fields in the structure array epi_1 containing 1-plot information, that is, execute epi_1[m].count=0; epi_1[m].time=0, where 1≤m≤n;

[0043] epi_1 is a structure array of length n, and the element epi_1[m] represents the 1-plot coded as m, and contains 2 data fields:

[0044] The count field represents 1-episode count;

[0045] The time field indicates the timestamp of the occurrence of 1-episode.

[0046] ③Ini...

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Abstract

The invention relates to a method for mining the lowest occurrence frequency episode from an event sequence, which is characterized by extending the low-order frequency episode step by step so as to directly generate a high-order frequency episode. In the method for finding and counting the lowest occurrence frequency of an episode, the lowest occurrence frequency of a 2-episode is found and counted by establishing an episode matrix and setting corresponding modification states on episode matrix elements, and the lowest occurrence frequency of a k-episode is found and counted by carrying out the timestamp-queue based extension on a frequency 2-episode. In the method for mining the episode by establishing an episode tree and using same node chains and Hash chains, the episode extension time and the occupied memory space are saved, and data need to be scanned once in the process of mining without generating a candidate episode set so that the mining efficiency is high and the less memory space is occupied. The method for mining the episode by establishing the episode tree and using same node chains and Hash chains has good characteristic that the mining time and the mining cost do not change obviously along with the frequency number threshold and can be further used for mining the episode from an event flow.

Description

Technical field [0001] The present invention belongs to temporal data mining technology, and specifically relates to a method and system for mining frequent episodes of event sequences based on the same node chain and hash chain. Background technique [0002] As sensors and RFID (Radio Frequency Identification, RFID) and other electronic data gathering equipment (EDGE) are widely used in many fields such as supply chain management, environmental monitoring, and the Internet of Things, a large number of incidents have occurred Types of data, Complex Event Processing (CEP) technology has attracted more and more attention and attention, and has gradually become a new research hotspot in the database field following data flow. Frequent episode mining is an important research content of CEP. Its methods and technologies can be applied in many aspects, such as network intrusion detection, financial events and stock trend analysis, telecommunication network alarms, and the Internet of T...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 林树宽乔建忠
Owner NORTHEASTERN UNIV
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