KS-Diff: a key structure based difference detection method for process models

Jiaxing Wang; Jianchao Lu; Bin Cao; Jing Fan; Dapeng Tan

doi:10.1109/ICWS.2019.00073

KS-Diff: a key structure based difference detection method for process models

Jiaxing Wang, Jianchao Lu, Bin Cao, Jing Fan, Dapeng Tan

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

2 Citations (Scopus)

Abstract

Detecting difference between two process models is a recurrent operation in business process management. A process model has multiple features, such as structure, behavior, and resource. Most of the existing methods only focus on one feature, which results in the loss of information in terms of other features. To provide more information on process difference to users, this paper proposes KS-Diff which can detect both structural and behavioral differences between two process models. First, the process models are transformed into their corresponding task-based process structure trees (TPSTs). Then, the one-hot codes are used to encode all leaf nodes of TPST, and the non-leaf nodes are encoded by the combination of one-hot codes of their child nodes. Next, the common key structure of two process models is extracted based on the one-hot encoding. Finally, the structural and behavioral differences are extracted on the basis of this common key structure. The efficiency study is provided to show the efficiency of KS-Diff.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services
Editors	Elisa Bertino, Carl K. Chang, Peter Chen, Ernesto Damiani, Michael Goul, Katsunori Oyama
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	408-412
Number of pages	5
ISBN (Electronic)	9781728127170
DOIs	https://doi.org/10.1109/ICWS.2019.00073
Publication status	Published - 2019
Event	26th IEEE International Conference on Web Services, ICWS 2019 - Milan, Italy Duration: 8 Jul 2019 → 13 Jul 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services

Conference

Conference	26th IEEE International Conference on Web Services, ICWS 2019
Country/Territory	Italy
City	Milan
Period	8/07/19 → 13/07/19

Keywords

Key structure
One-hot encoding
Process difference
Process model

Access to Document

10.1109/ICWS.2019.00073

Cite this

Wang, J., Lu, J., Cao, B., Fan, J., & Tan, D. (2019). KS-Diff: a key structure based difference detection method for process models. In E. Bertino, C. K. Chang, P. Chen, E. Damiani, M. Goul, & K. Oyama (Eds.), Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services (pp. 408-412). (Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICWS.2019.00073

Wang, Jiaxing ; Lu, Jianchao ; Cao, Bin et al. / KS-Diff : a key structure based difference detection method for process models. Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services. editor / Elisa Bertino ; Carl K. Chang ; Peter Chen ; Ernesto Damiani ; Michael Goul ; Katsunori Oyama. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2019. pp. 408-412 (Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services).

@inproceedings{c99cd1db490547e99814f01daa79e113,

title = "KS-Diff: a key structure based difference detection method for process models",

abstract = "Detecting difference between two process models is a recurrent operation in business process management. A process model has multiple features, such as structure, behavior, and resource. Most of the existing methods only focus on one feature, which results in the loss of information in terms of other features. To provide more information on process difference to users, this paper proposes KS-Diff which can detect both structural and behavioral differences between two process models. First, the process models are transformed into their corresponding task-based process structure trees (TPSTs). Then, the one-hot codes are used to encode all leaf nodes of TPST, and the non-leaf nodes are encoded by the combination of one-hot codes of their child nodes. Next, the common key structure of two process models is extracted based on the one-hot encoding. Finally, the structural and behavioral differences are extracted on the basis of this common key structure. The efficiency study is provided to show the efficiency of KS-Diff.",

keywords = "Key structure, One-hot encoding, Process difference, Process model",

author = "Jiaxing Wang and Jianchao Lu and Bin Cao and Jing Fan and Dapeng Tan",

year = "2019",

doi = "10.1109/ICWS.2019.00073",

language = "English",

series = "Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "408--412",

editor = "Elisa Bertino and Chang, {Carl K.} and Peter Chen and Ernesto Damiani and Michael Goul and Katsunori Oyama",

booktitle = "Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services",

address = "United States",

note = "26th IEEE International Conference on Web Services, ICWS 2019 ; Conference date: 08-07-2019 Through 13-07-2019",

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Wang, J, Lu, J, Cao, B, Fan, J & Tan, D 2019, KS-Diff: a key structure based difference detection method for process models. in E Bertino, CK Chang, P Chen, E Damiani, M Goul & K Oyama (eds), Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services. Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 408-412, 26th IEEE International Conference on Web Services, ICWS 2019, Milan, Italy, 8/07/19. https://doi.org/10.1109/ICWS.2019.00073

KS-Diff : a key structure based difference detection method for process models. / Wang, Jiaxing; Lu, Jianchao; Cao, Bin et al.

Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services. ed. / Elisa Bertino; Carl K. Chang; Peter Chen; Ernesto Damiani; Michael Goul; Katsunori Oyama. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 408-412 (Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - KS-Diff

T2 - 26th IEEE International Conference on Web Services, ICWS 2019

AU - Wang, Jiaxing

AU - Lu, Jianchao

AU - Cao, Bin

AU - Fan, Jing

AU - Tan, Dapeng

PY - 2019

Y1 - 2019

N2 - Detecting difference between two process models is a recurrent operation in business process management. A process model has multiple features, such as structure, behavior, and resource. Most of the existing methods only focus on one feature, which results in the loss of information in terms of other features. To provide more information on process difference to users, this paper proposes KS-Diff which can detect both structural and behavioral differences between two process models. First, the process models are transformed into their corresponding task-based process structure trees (TPSTs). Then, the one-hot codes are used to encode all leaf nodes of TPST, and the non-leaf nodes are encoded by the combination of one-hot codes of their child nodes. Next, the common key structure of two process models is extracted based on the one-hot encoding. Finally, the structural and behavioral differences are extracted on the basis of this common key structure. The efficiency study is provided to show the efficiency of KS-Diff.

AB - Detecting difference between two process models is a recurrent operation in business process management. A process model has multiple features, such as structure, behavior, and resource. Most of the existing methods only focus on one feature, which results in the loss of information in terms of other features. To provide more information on process difference to users, this paper proposes KS-Diff which can detect both structural and behavioral differences between two process models. First, the process models are transformed into their corresponding task-based process structure trees (TPSTs). Then, the one-hot codes are used to encode all leaf nodes of TPST, and the non-leaf nodes are encoded by the combination of one-hot codes of their child nodes. Next, the common key structure of two process models is extracted based on the one-hot encoding. Finally, the structural and behavioral differences are extracted on the basis of this common key structure. The efficiency study is provided to show the efficiency of KS-Diff.

KW - Key structure

KW - One-hot encoding

KW - Process difference

KW - Process model

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U2 - 10.1109/ICWS.2019.00073

DO - 10.1109/ICWS.2019.00073

M3 - Conference proceeding contribution

T3 - Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services

SP - 408

EP - 412

BT - Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services

A2 - Bertino, Elisa

A2 - Chang, Carl K.

A2 - Chen, Peter

A2 - Damiani, Ernesto

A2 - Goul, Michael

A2 - Oyama, Katsunori

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

Y2 - 8 July 2019 through 13 July 2019

ER -

Wang J, Lu J, Cao B, Fan J, Tan D. KS-Diff: a key structure based difference detection method for process models. In Bertino E, Chang CK, Chen P, Damiani E, Goul M, Oyama K, editors, Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2019. p. 408-412. (Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services). https://doi.org/10.1109/ICWS.2019.00073

KS-Diff: a key structure based difference detection method for process models

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