A Method for Goal Model Repair Based on Process Mining

Horita, Hiroki; Hirayama, Hideaki; Hayase, Takeo; Tahara, Yasuyuki; Ohsuga, Akihiko

doi:10.1109/snpd.2019.8935771

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…The computational techniques refer to those that implement simulations, including searches in graphs and procedural algorithms. This category encompasses 33% percent of the papers, such as the works by Borgianni et al [45], Mukhi and Nirmal [37], and Horita et al [47]. The artificial intelligence category contained 39% of the papers and refers to those works that also implemented a learning technique in at least one of the steps of their methods.…”

Section: Discussionmentioning

confidence: 99%

“…Decision support can come on other fronts of business processes, for example, by providing tools and aligning goals of business analysts with other teams. In this sense, Horita et al [47] proposed a method for repairing goal models based on the adjustments of the equivalent BP. A goal model is helpful for outlining company objectives and, therefore, has a complementary relationship with business process models.…”

Section: Decision Support Methodsmentioning

confidence: 99%

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Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review

et al. 2022

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Companies are usually overloaded with data that they may not know how to take advantage of. On the other hand, artificial intelligence (AI) techniques are known to “keep learning” as the data increase. In this context, our research question emerges: what AI-based methods, in the literature, could be used to automatize business processes and support the decision-making processes of companies? To fill this gap, in this paper, we performed a review of the literature to identify these techniques. We ensured the usage of methods since they allowed reproducibility and extensions. We applied our search string in the Scopus and Web of Science databases and discovered 21 relevant papers pertaining to our question. In these papers, we identified methods that automated tasks and helped analysts make assertive decisions when designing, extending, or reengineering business processes. The authors applied diverse AI techniques, such as K-means, Bayesian networks, and swarm intelligence. Our analysis provides statistics about the techniques and problems being tackled and point to possible future directions.

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Section: Discussionmentioning

confidence: 99%

Section: Decision Support Methodsmentioning

confidence: 99%

Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review

et al. 2022

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“…With the insights gained from Artificial Intelligence and Machine Learning, organizations can then identify opportunities for process optimization. Process Mining bridges the gap between traditional model-based process analysis and data-centric analysis techniques such as Machine Learning and Data Mining [17,19,20,21].…”

Section: Methodsmentioning

confidence: 99%

The process mining method approach to analyze users’ behavior of internet in the Local Area Network of Sriwijaya University

Jambak

Mohruni

Jambak

et al. 2022

Sinergi

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The Sriwijaya University internet network management unit does not yet have a standard formulation for implementing Bandwidth Management & Bandwidth Allocation. To provide the best service, they apply the Best-Effort Service concept. As a result, it requires a relatively large network capacity and bandwidth provision so that it has an impact on costs. Therefore, it is necessary to know how users use internet bandwidth as the basic principle of Bandwidth Management & Bandwidth Allocation. This study has completed how to determine the behavior of internet users on the campus LAN as a reason to evaluate internet bandwidth usage. With the Process Mining method, process mapping has been carried out for all access to internet usage from all faculties. As a result, the factors that characterize and need to be considered in bandwidth management are obtained. In order of significance are Total Access Length, Average Variance, Number of User Case IDs, Number of Non-Academic Ports, Number of Academic Ports, Number of Access Frequency, Number of Events, and Number of Ports of Service.

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“…Although much research on goal orientation has been done in the field of requirements engineering [13] [14], it has not been done much in the field of process mining. Process mining methods that use goal orientation include goal-oriented conformance checking [15], goal repair [16], agent goal learning [17], aligning goal and business process [18], [19], automatic determination of KPI threshold values [20], discovering requirements [21] and variant analysis [22].…”

Section: Goal-oriented Process Miningmentioning

confidence: 99%

Comparison of Goal-Oriented Business Process Model Repair and Discovery

Horita

Takei

2023

International Journal of Service and Knowledge Management

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Process mining is a technology that extracts useful knowledge from event logs output from information systems and utilizes it for business process analysis and improvement. Conventional process mining approaches do not take into account information about organizational goals, and thus may output process models that inhibit the goal of the organization, for example, "to reduce cost". To solve such problems, goal-oriented process discovery method was proposed as an existing research. On the other hand, one of the methods to generate process models is process model repair. This method uses a process model and an event log as input, and repairs the existing process model to reproduce all the behaviors observed in the event log. However, the existing process model repair methods do not take into account the information about goals. Therefore, in this paper, we propose a goal-oriented process model repair method. It is easy to visually identify and compare which parts of the existing process model satisfy the goal satisfaction and which parts do not satisfy the goal. In addition, the structure of the model is simpler and closer to the initial model, and its effectiveness can be demonstrated. The effectiveness of the model was confirmed by experimental results.

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A Method for Goal Model Repair Based on Process Mining

Cited by 7 publications

References 13 publications

Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review

Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review

The process mining method approach to analyze users’ behavior of internet in the Local Area Network of Sriwijaya University

Comparison of Goal-Oriented Business Process Model Repair and Discovery

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