TY - GEN
T1 - Structural descriptions of process models based on goal-oriented unfolding
AU - Qian, Chen
AU - Wen, Lijie
AU - Wang, Jianmin
AU - Kumar, Akhil
AU - Li, Haoran
N1 - Funding Information:
The work was supported by the National Key Research and Development Program of China (No. 2016YFB1001101) and the National Nature Science Foundation of China (Nos. 61472207, 61325008 and 71690231).
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Business processes are normally managed by designing, operating and analysing corresponding process models. While delivering these process models, an understanding gap arises depending on the degree of different users’ familiarity with modeling languages, which may slow down or even stop the normal functioning of processes. Therefore, a method for automatically generating texts from process models was proposed. However, the current method just involves ordinary model patterns so that the coverage of the generated text is too low and information loss exists. In this paper, we propose an improved transformation algorithm named Goun to tackle this problem of describing the process models automatically. The experimental results demonstrate that the Goun algorithm not only supports more elements and complex structures, but also remarkably improves the coverage of generated text.
AB - Business processes are normally managed by designing, operating and analysing corresponding process models. While delivering these process models, an understanding gap arises depending on the degree of different users’ familiarity with modeling languages, which may slow down or even stop the normal functioning of processes. Therefore, a method for automatically generating texts from process models was proposed. However, the current method just involves ordinary model patterns so that the coverage of the generated text is too low and information loss exists. In this paper, we propose an improved transformation algorithm named Goun to tackle this problem of describing the process models automatically. The experimental results demonstrate that the Goun algorithm not only supports more elements and complex structures, but also remarkably improves the coverage of generated text.
UR - http://www.scopus.com/inward/record.url?scp=85021226038&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-59536-8_25
DO - 10.1007/978-3-319-59536-8_25
M3 - Conference contribution
AN - SCOPUS:85021226038
SN - 9783319595351
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 397
EP - 412
BT - Advanced Information Systems Engineering - 29th International Conference, CAiSE 2017
A2 - Dubois, Eric
A2 - Pohl, Klaus
PB - Springer Verlag
T2 - Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering, CAiSE-Forum-DC 2017
Y2 - 12 June 2017 through 16 June 2017
ER -