Service Discovery from Observed Behavior while Guaranteeing Deadlock Freedom in Collaborations
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.
Vol. 8274: Lecture Notes in Computer Science. , Berlin, Heidelberg : Springer, 2013
, , , 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
, , , UnconstrainedMiner: Efficient Discovery of Generalized Declarative Process Models / . 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
'Learning high-level process models from event data', Doctor of Philosophy, Department of Mathematics and Computer Science
, 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
, , , 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
, , , 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
, , 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
, , in : Business Intelligence. Third European Summer School, eBISS 2013, Dagstuhl Castle, Germany, July 7-12, 2013, Tutorial Lectures. Vol. 172: Lecture Notes in Business Information Processing.: Springer, 2014. P. 33-76.
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
, , , , 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
, , , 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
, , 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
, , , 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
Discovering architecture-aware and sound process models of multi-agent systems: a compositional approach
, , et al., Software and Systems Modeling 2022
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
, , 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
, , , in : Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers. Vol. 11832.: Cham : Springer, 2019. P. 401-410.
Added: October 24, 2019
, , 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
, , 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
, , 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
, , Proceedings of the Institute for System Programming of the RAS 2019 Vol. 31 No. 4 P. 139-150
UML Activity Diagrams are widely used models for representing software processes. Models built from event logs, recorded by information systems, can provide valuable insights into real flows in processes and suggest ways of improving those systems. This paper proposes a novel method for mining UML Activity Diagrams from event logs. The method is based on ...
Added: October 28, 2019
, , et al., , in : Application and Theory of Petri Nets and Concurrency. 36th International Conference, PETRI NETS 2015, Brussels, Belgium, June 21-26, 2015, Proceedings. Issue 9115.: Switzerland : Springer, 2015. P. 287-308.
Process mining techniques aim to analyze and improve conformance and performance of processes using event data. Process discovery is the most prominent process-mining task: A process model is derived based on an event log. The process model should be able to capture causalities, choices, concurrency, and loops. Process discovery is very challenging because of trade-offs ...
Added: June 11, 2015
, Форсайт 2013
This paper represents an approach to development and implementation of the formal model of technological roadmapping (TRM). The research was carried out based on the analysis of the best practices in the domain. It integrates the experience of a wide range of TRM projects. The proposed model provides basis for developing tools for TRM automation, ...
Added: August 12, 2013
, , Proceedings of the Institute for System Programming of the RAS 2019 Vol. 31 No. 4 P. 151-162
Event logs of software systems are used to analyse their behaviour and inter-component interaction. Artificial event logs with desirable specifics are needed to test algorithms supporting this type of analysis. Recent methods allow to generate artificial event logs by simulating ordinary Petri nets. In this paper we present the algorithm generating event logs for Petri ...
Added: October 14, 2019
Modelling and Validation of Trading and Multi-Agent Systems: An Approach Based on Process Mining and Petri Nets
, , , in : ICPM Doctoral Consortium 2019. Vol. 2432: CEUR Workshop Proceedings.: CEUR-WS.org, 2019. Ch. 4. P. 1-12.
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
, , , in : Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers. Vol. 10716.: Cham : Springer, 2018. P. 371-377.
In this paper we present an approach for searching sub-traces in event logs, generated by information systems. Our technique is heavily based on the Aho-Corasick algorithm, and extends it with simultaneous search on several event log traces. The computational complexity of the proposed approach was estimated. Moreover, the approach was implemented and verified on real-life ...
Added: October 11, 2017
, , Прикаспийский журнал: управление и высокие технологии 2014 № 2 (26) С. 127-137
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a ...
Added: February 27, 2014