Optimization method based on big data in business process management

被引：2

作者：

Li, Tingshun ^{[1
]}

Xiong, Li ^{[4
]}

Dong, Aiqiang ^{[4
]}

Liu, Ze-San ^{[4
]}

Tan, Wen ^{[2
,3
]}

机构：

[1] North China Elect Power Univ, Comp Applicat Technol, Beijing, Peoples R China

[2] North China Elect Power Univ, Fac Power Engn Dept, Beijing, Peoples R China

[3] North China Elect Power Univ, Automat Dept, Beijing, Peoples R China

[4] Beijing China Power Informat Technol Co Ltd, State Grid Informat & Telecommun Grp, Beijing, Peoples R China

来源：

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / Suppl 3期

基金：

中国国家自然科学基金;

关键词：

Data-driven; Big data; BPM; Euclidean distance; Automatic process flow; SUPPORT;

D O I：

10.1007/s10586-017-1243-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents the current research status of business process management (BPM) based on data drive, and then explains how to apply big data technology to analyze the BPM Data and build BPM knowledgebase in order to guide, optimize and forecast the business process. According the characteristics of the BPM data, the paper proposes a new method based on big data-driven according by key words and process flow (KW + PF), and shows the processing steps. In the furthermore, an automatic process flow with a certain intelligence is designed which is based on a loosely coupled configurable flow engine, meanwhile is guided by the knowledgebase. At last, this paper researches and analyzes how to apply the automatic intelligent process flow attach to the current BPM system and to minimize the disturbance. Moreover, developing trend and research challenge of BPM-driven by big data are illustrated.

引用

页码：S5357 / S5365

页数：9

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