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Service Discovery from Observed Behavior while Guaranteeing Deadlock Freedom in Collaborations
P. 358-373.
Müller R., Stahl C., van der Aalst W., Westergaard M.
Process discovery techniques can be used to derive a process model from observed example behavior (i.e., an event log). As the observed behavior is inherently incomplete and models may serve different purposes, four competing quality dimensions—fitness, precision, simplicity, and generalization—have to be balanced to produce a process model of high quality.
In this paper, we investigate the discovery of processes that are specified as services. Given a service S and observed behavior of a service P interacting with S, we discover a service model of P. Our algorithm balances the four quality dimensions based on user preferences. Moreover, unlike existing discovery approaches, we guarantees that the composition of S and P is deadlock free. The service discovery technique has been implemented in ProM and experiments using service models of industrial size demonstrate the scalability or our approach.
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English
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In book
Vol. 8274: Lecture Notes in Computer Science. , Berlin, Heidelberg : Springer, 2013
Катаева В. М., Kalenkova A. A., , in : Proceedings of the 8th Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2014). : M. : -, 2014. P. 83-87.
This work is dedicated to one of the most urgent problems in the field of process mining. Process mining is a technique that offers plenty of methods for the discovery and analysis of business processes based on event logs. However, there is a lack of real process models and event logs, which can be used ...
Added: June 3, 2014
Kirill Artamonov, Irina Lomazova, , in : Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science. Vol. 1086.: Springer, 2020.
One of the goals of business process audit is to check the conformance between the process model and real process behavior represented in the form of event log. Conformance checking procedure may detect such discrepancies as undesired behavior or behavior shifts. There are several proven methods for performing this procedure, namely, token replay and trace alignments. One more method employs partially synchronized ...
Added: October 24, 2019
Kalenkova A. A., TU/e Eindhoven, 2018
Information systems in different domains, such as healthcare, tourism, banking, government and others, record operational behavior in the form of event logs. The process mining discipline offers dozens of techniques to discover, analyze, and visualize processes running in information systems, based on their event logs. The representational bias (the language for processes representation) plays an ...
Added: June 14, 2018
Kirill Artamonov, Irina Lomazova, , in : 21st IEEE Conference on Business Informatics (CBI). : IEEE Computer Society, 2019. P. 551-558.
Checking conformance between a process model and an event log, which records information about a current process behavior, is a widely used technique for business process audit. It allows discovering changes in the behavior represented by the model. There are several methods to perform conformance checking: most of them are based on 'token replay' and ...
Added: August 28, 2019
Westergaard M., Stahl C., Reijers H., / Eindhoven University of Technology. Series BPM-13-28 "BPM Center Report". 2013. No. 13-28.
Process discovery techniques derive a process model from observed behavior (e.g., event logs). In case of less structured processes, declarative models have notable advantages over procedural models. A declarative model consists of a set of temporal constraints over the activities in the event log. In this paper, we address three limitations of current discovery techniques: ...
Added: March 21, 2014
A. A. Sherstyugina, R. A. Nesterov, Proceedings of the Institute for System Programming of the RAS 2023 Vol. 35 No. 3 P. 11-32
The structure of a process model directly discovered from an event log of a multi-agent system often does not reflect the behavior of individual agents and their interactions. We suggest analyzing the relations between events in an event log to localize actions executed by different agents and involved in their asynchronous interaction. Then, a process ...
Added: October 31, 2023
Begicheva A., Lomazova I. A., Nesterov R., / Cornell University. Series Computer Science "arxiv.org". 2023.
Process mining is a field of computer science that deals with discovery and analysis of process models based on automatically generated event logs. Currently, many companies use this technology for optimization and improving their processes. However, a discovered process model may be too detailed, sophisticated and difficult for experts to understand. In this paper, we ...
Added: March 31, 2023
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Recently, process mining emerged as a new scientific discipline on the interface between process models and event data. On the one hand, conventional Business Process Management (BPM) and Workflow Management (WfM) approaches and tools are mostly model-driven with little consideration for event data. On the other hand, Data Mining (DM), Business Intelligence (BI), and Machine ...
Added: October 17, 2014
Roman A. Nesterov, Irina A. Lomazova, , in : Proceedings of the MACSPro Workshop 2019. Vol. 2478: CEUR Workshop Proceedings.: CEUR-WS.org, 2019. P. 62-73.
Process models discovered from event logs of multi-agent systems may be complicated and unreadable. To overcome this problem, we suggest using a compositional approach. A system model is composed from agent models w.r.t. an interface. Morphisms guarantee that composition of correct models is correct. This study contributes to the practical implementation of the morphism-based compositional ...
Added: October 10, 2019
Begicheva A.K., Lomazova I.A., Modeling and Analysis of Information Systems 2017 Vol. 24 No. 2 P. 125-140
Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of discovering a high-level business process model from a low-level event log, i.e. automatic synthesis of process models based on the information stored in event logs of ...
Added: May 6, 2017
Antonina K. Begicheva, Lomazova I. A., , in : Proceedings of the 8th Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2014). : M. : -, 2014. P. 77-82.
Process mining is a new technology, that provides us a variety of methods to discover, monitor and improve real processes by extracting knowledge from event logs. The two most prominent process mining tasks are process discovery and conformance checking. Conformance checking deals with diagnosing and quantifying discrepancies between observed behavior, represented in event logs, and ...
Added: June 2, 2014
Kalenkova A. A., van der Aalst W., Lomazova I. A. et al., , in : MODELS '16 Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems. : NY : ACM, 2016. P. 123-123.
Process mining is an emerging discipline incorporating methods and tools for the analysis of system/process executions captured in the form of event logs. Traditionally process mining can be divided into three research areas: discovery (construction of process models from event logs), conformance checking (finding log and model deviations), and enhancement of existing process models with ...
Added: October 8, 2016
Kalenkova A. A., van der Aalst W., Lomazova I. A. et al., Software and Systems Modeling 2017 Vol. 16 No. 4 P. 1019-1048
Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining techniques used to discover process models from event logs, find log and model deviations, and ...
Added: June 11, 2015
Kalenkova A. A., Lomazova I. A., van der Aalst W., , in : Application and Theory of Petri Nets and Concurrency. 35th International Conference, PETRI NETS 2014, Tunis, Tunisia, June 23-27, 2014, Proceedings. Vol. 8489: Lecture Notes in Computer Science.: Berlin : Springer, 2014. P. 71-90.
Process mining aims to discover and analyze processes by extracting information from event logs. Process mining discovery algorithms deal with large data sets to learn automatically process models. As more event data become available there is the desire to learn larger and more complex process models. To tackle problems related to the readability of the ...
Added: July 3, 2014
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Added: October 24, 2019
van der Aalst W., , in : Proceedings of the 2013 Federated Conference on Computer Science and Information Systems. Vol. 1: Annals of Computer Science and Information Systems.: Warsz. : Polskie Towarzystwo Informatyczne, 2013. P. 1-10.
Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining – an emerging scientific discipline relating modeled and observed behavior. The relevance of process mining is increasing as more and more event data become available. The increasing volume of such data (“Big Data”) provides both ...
Added: November 14, 2013
Begicheva A., Lomazova I. A., Modeling and Analysis of Information Systems 2015 Vol. 22 No. 3 P. 392-403
Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of models and event logs conformance checking. Conformance checking is intensively studied in the frame of process mining research, but only models and event logs of the ...
Added: August 5, 2015
Nesterov R., Bernardinello L., Lomazova I. A. et al., Software and Systems Modeling 2023 Vol. 22 P. 351-375
A process model discovered from an event log of a multi-agent system often does not fully cover certain viewpoints of its architecture. We consider those concerned with the structure of a model explicitly reflecting agent behavior and interactions. The direct discovery from an event log of a multi-agent system may result in an unclear model ...
Added: May 5, 2022
van der Aalst W., , in : Asia Pacific Conference on Business Process Management. First Asia Pacific Conference, AP-BPM 2013, Beijing, China, August 29-30, 2013, Selected Papers. Vol. 159: Lecture Notes in Business Information Processing .: Dordrecht, L., Heidelberg, NY : Springer, 2013. P. 1-22.
Recent breakthroughs in process mining research make it possible to discover, analyze, and improve business processes based on event data. The growth of event data provides many opportunities but also imposes new challenges. Process mining is typically done for an isolated well-defined process in steady-state. However, the boundaries of a process may be fluid and ...
Added: November 14, 2013
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This paper presents our research on trading and multi-agent systems. Trading systems support the processes of buying/selling financial instruments between traders, so the validation of their correctness is a crucial task. Conversely, multi-agent systems is a current topic of interest within the analysis of interactive processes. We use Petri nets as the formalism for system ...
Added: August 28, 2019
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Trading systems are software platforms that support the exchange of securities (e.g., company shares) between participants. In this paper, we present a method to search for deviations in trading systems by checking conformance between colored Petri nets and event logs. Colored Petri nets (CPNs) are an extension of Petri nets, a formalism for modeling of ...
Added: January 31, 2024
Lyadova L. N., Платунов А. И., Информатизация и связь 2024 № 1 С. 84-89
Summary. The goal of the project is developing tools for generating and preprocessing event logs for process analysis using Process Mining methods. The implementation approach is based on low-code principles. Users should be able to develop their own rules for generating and processing event logs, including additional attributes, – event series. It is based on ...
Added: January 19, 2024
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Process mining is a relatively new research field, offering methods of business processes analysis and improvement, which are based on studying their execution history (event logs). Conformance checking is one of the main sub-fields of process mining. Conformance checking algorithms are aimed to assess how well a given process model, typically represented by a Petri ...
Added: September 12, 2016
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Existing process mining methods allow to investigate processes in different domains. Besides mandatory event attributes like as identifier, activity, and timestamp, additional event attributes can be present in data sources. The analysing dynamics of changing the values of additional attributes allows to get important information on the system. The applications must be developed by programmers ...
Added: November 22, 2023