Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Deviation reduction-based big data transaction model analysis and restoration method

A model analysis and repair method technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve the complex execution process, the model repair method cannot accurately find and solve, and cannot guarantee that the log is consistent with the model Sexuality and other issues, to achieve good results, the effect of a reasonable design

Active Publication Date: 2018-08-14
SHANDONG UNIV OF SCI & TECH
View PDF3 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Existing model repair methods are mainly based on model calibration to discover the deviation between the log and the model to achieve the purpose of model repair, in which the model calibration is to replay the track in the log to the model, and then discover the gap between the model and the real business. The model repair method based on model calibration has certain guiding and reference significance for model repair, but in the process of repairing the big data transaction model, in the case of log and model fitting, when multiple parallel branches in the transaction model When there is a deviation between them, the model repair method based on model calibration cannot accurately discover and solve
[0005] The problem solved by the iterative process discovery technology is similar to the model repair problem. In the process of repairing the big data transaction model, the implementation process of the iterative process discovery technology is complicated and cannot guarantee the consistency between the log and the model after repair, which may easily lead to repair. The final process model only allows the behavior recorded in the log to occur, that is, the phenomenon of overfitting occurs

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Deviation reduction-based big data transaction model analysis and restoration method
  • Deviation reduction-based big data transaction model analysis and restoration method
  • Deviation reduction-based big data transaction model analysis and restoration method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0083] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0084] 1. Related concepts

[0085] 1.1, multiset, sequence

[0086] is a collection, there is a mapping in representative set The set of all multisets on ; for example multiset B 1 :=[],B 2 :=[a],B 3 :=[a,b,b,c,b,a],B 4 :=[a 2 ,c,b,b 2 ];sequence |σ| represents the length of the sequence σ, |σ|:=n.

[0087] 1.2. Petri net

[0088] Petri net is a model used to describe distributed systems; the triple N:=(P,T,F) is called a Petri net, P, T are two disjoint finite sets, they are the network N The basic element set, P is called the place set, T is called the transition set, and F is the flow relationship of the network N.

[0089] Let N:=(P,T,F) be a Petri net, for x∈P∪T, record

[0090]

[0091]

[0092] We call ·x the former set or input set of x, and x· the posterior set or output set of x.

[0093] 1.3, identi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a deviation reduction-based big data transaction model analysis and restoration method, and belongs to the field of business process management. The method specifically comprises the following steps of discovering a deviation set Rd between event logs and a model through a reachable marking graph-based deviation discovery method; and according to the deviation set Rd, obtaining an adjacent side relationship difference set Rp, and obtaining an adjacent side relationship difference sequence set PS. Through the deviation reduction-based model restoration method, effectivedeviation-based model restoration is realized; and a restoration result is subjected to model fitting degree, accuracy, conciseness and time complexity assessment to verify the validity of the method.

Description

technical field [0001] The invention belongs to the field of business process management, and in particular relates to a big data transaction model analysis and repair method based on deviation reduction. Background technique [0002] With the emergence of massive data, the value of data has been recognized by more and more industries and fields. Big data transactions have become a new type of data circulation means. During the construction of big data trading platforms, self-owned data sales, data processing Various transaction modes such as resale and data transaction platform services. How to discover and solve the deviation between actual execution and business rules in the big data transaction process in time is a huge challenge for the big data transaction process. Business process management realizes the comprehensive management of the integration of various business links by modeling, managing, monitoring and optimizing the entire life cycle of business processes. ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/50G06Q10/10
CPCG06Q10/103G06F30/22
Inventor 张鹏郭艺戚梅
Owner SHANDONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com