A Comprehensive Process Similarity Measure Based on Models and Logs

Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enoug...
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Autor*in:	Changhong Zhou [verfasserIn] Cong Liu [verfasserIn] Qingtian Zeng [verfasserIn] Zedong Lin [verfasserIn] Hua Duan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Business process process similarity process model process log

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 69257-69273
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:69257-69273

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2018.2885819

Katalog-ID:	DOAJ013545868

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allfieldsGer	10.1109/ACCESS.2018.2885819 doi (DE-627)DOAJ013545868 (DE-599)DOAJ0caf638976c54484b022a19f7368227c DE-627 ger DE-627 rakwb eng TK1-9971 Changhong Zhou verfasserin aut A Comprehensive Process Similarity Measure Based on Models and Logs 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art. Business process process similarity process model process log Electrical engineering. Electronics. Nuclear engineering Cong Liu verfasserin aut Qingtian Zeng verfasserin aut Zedong Lin verfasserin aut Hua Duan verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 69257-69273 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:69257-69273 https://doi.org/10.1109/ACCESS.2018.2885819 kostenfrei https://doaj.org/article/0caf638976c54484b022a19f7368227c kostenfrei https://ieeexplore.ieee.org/document/8611068/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 69257-69273
allfieldsSound	10.1109/ACCESS.2018.2885819 doi (DE-627)DOAJ013545868 (DE-599)DOAJ0caf638976c54484b022a19f7368227c DE-627 ger DE-627 rakwb eng TK1-9971 Changhong Zhou verfasserin aut A Comprehensive Process Similarity Measure Based on Models and Logs 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art. Business process process similarity process model process log Electrical engineering. Electronics. Nuclear engineering Cong Liu verfasserin aut Qingtian Zeng verfasserin aut Zedong Lin verfasserin aut Hua Duan verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 69257-69273 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:69257-69273 https://doi.org/10.1109/ACCESS.2018.2885819 kostenfrei https://doaj.org/article/0caf638976c54484b022a19f7368227c kostenfrei https://ieeexplore.ieee.org/document/8611068/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 69257-69273
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source	In IEEE Access 7(2019), Seite 69257-69273 volume:7 year:2019 pages:69257-69273
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authorswithroles_txt_mv	Changhong Zhou @@aut@@ Cong Liu @@aut@@ Qingtian Zeng @@aut@@ Zedong Lin @@aut@@ Hua Duan @@aut@@
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callnumber-first	T - Technology
author	Changhong Zhou
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topic_title	TK1-9971 A Comprehensive Process Similarity Measure Based on Models and Logs Business process process similarity process model process log
topic	misc TK1-9971 misc Business process misc process similarity misc process model misc process log misc Electrical engineering. Electronics. Nuclear engineering
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title	A Comprehensive Process Similarity Measure Based on Models and Logs
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title_sort	comprehensive process similarity measure based on models and logs
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title_auth	A Comprehensive Process Similarity Measure Based on Models and Logs
abstract	Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art.
abstractGer	Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art.
abstract_unstemmed	Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art.
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title_short	A Comprehensive Process Similarity Measure Based on Models and Logs
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score	7.4008465

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