Graph mining and graph distance-based flow recommendation method

A technology of process recommendation and graph mining, applied in the field of process automation, which can solve the problems that the practicability of the process recommendation method is relatively limited and cannot support complex processes.

Active Publication Date: 2013-11-20
ZHEJIANG UNIV
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Problems solved by technology

[0005] Aiming at the disadvantages of the existing process recommendation method, such as limited practicality and being unable to support complex processes including loop structures, the present invention provides a novel process recommendation method based on graph mining and graph distance

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  • Graph mining and graph distance-based flow recommendation method
  • Graph mining and graph distance-based flow recommendation method
  • Graph mining and graph distance-based flow recommendation method

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Embodiment 1

[0044] The process recommendation method based on graph mining and graph distance is used to realize the automation of process modeling. The system architecture is as follows: figure 1 , including the following modules:

[0045] User interface 1: This module mainly deals with user input and output, and provides interactive functions for users, including uploading of process files (process sets) and process modeling by modelers.

[0046] Preprocessing module 2: This module abstracts the input process set into a directed graph form, and the process set is a collection of several processes. The process mentioned here includes: process flow, that is, various processes from raw materials to finished products Arranged procedures; business process, that is, the process of completing a complete business behavior by two or more business steps, which can be called a process, note that it is two or more business steps; and business process, that is, things in progress The arrangement an...

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Abstract

The invention relates to the field of flow automation, and discloses a graph mining and graph distance-based flow recommendation method. The method specifically comprises the following steps: preprocessing, i.e., abstractly labeling an input flow set in the form of a directed graph to obtain a flow sub-graph; discovering a pattern, i.e., decomposing a set output by the preprocessing step to obtain an upstream sub-graph, a candidate node set and confidence by a sub-graph mining and decomposing module, registering the upstream sub-graph, the candidate node set and the confidence as data entries in a pattern list; recommending a flow, i.e., acquiring a reference flow by a recommendation module, comparing the reference flow with the upstream sub-graph in the pattern list, selecting the most matched data entry, and outputting the candidate node corresponding to the most matched data entry as the recommended flow. The method has the advantages of high recommendation efficiency, smaller calculation complexity of the algorithm, high recommendation accuracy, capability of supporting the processing of a complex structure flow and higher application value.

Description

technical field [0001] The invention relates to the field of process automation, in particular to a process recommendation method based on graph mining and graph distance. Background technique [0002] Fast and efficient business process modeling is an important criterion to measure whether a modern enterprise can cope with the changing enterprise environment. However, business process modeling is an extremely complex and time-consuming task, which requires modelers not only to have professional domain knowledge, but also to be familiar with the execution process, execution sequence and exception handling of various business activities. Currently, business intelligence (BI)-based techniques, such as process mining and process retrieval, are used to assist process modeling. Process mining technology uses data mining technology to discover processes from the process library or event log as a modeling reference; process retrieval technology retrieves similar process fragments ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06
Inventor 邓水光王东京李莎吴健李莹尹建伟吴朝晖
Owner ZHEJIANG UNIV
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