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- ArticleSeptember 2024
Object Synchronizations and Specializations with Silent Objects in Object-Centric Petri Nets
AbstractProcesses involve interacting objects of different types, such as orders, items and machines. Object-centric event logs capture the execution of activities with the involved objects in such processes. Discovery algorithms use these logs to ...
- abstractJune 2023
Towards a Framework for Data Pipeline Discovery
SIGMOD '23: Companion of the 2023 International Conference on Management of DataPages 293–294https://doi.org/10.1145/3555041.3589395With the recent developments of Internet of Things (IoT) and cloudbased technologies, massive amounts of data are generated by heterogeneous sources and stored through dedicated cloud solutions. Often organizations generate much more data than they are ...
- posterJune 2023
Discovering Process Models that Support Desired Behavior and Avoid Undesired Behavior
SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied ComputingPages 365–368https://doi.org/10.1145/3555776.3577818Process discovery is one of the primary process mining tasks and starting point for process improvements using event data. Existing process discovery techniques aim to find process models that best describe the observed behavior. The focus can be on ...
- research-articleJanuary 2022
Applying process mining to minimise order waiting time of FitBox
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Volume 7, Issue 3-4Pages 190–233https://doi.org/10.1504/ijkedm.2022.126068The main objective of the paper is to investigate the reasons why a lot of complaints (by customers) have been made against the quality of 'food delivery service' in one of the FitBox branches. During the COVID-19 pandemic, it is important for the FitBox ...
- research-articleJanuary 2022
Chaotic activities recognising during the pre-processing event data phase
International Journal of Business Intelligence and Data Mining (IJBIDM), Volume 20, Issue 4Pages 412–439https://doi.org/10.1504/ijbidm.2022.123213Process mining aims at obtaining insights into business processes by extracting knowledge from event data. Indeed, the quality of events is a crucial element for generating process models, to reflect business process reality. To do so, pre-processing ...
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- research-articleMarch 2020
Event-log abstraction using batch session identification and clustering
SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied ComputingPages 36–44https://doi.org/10.1145/3341105.3373861Process-Mining techniques aim to use event data about past executions to gain insight into how processes are executed. While these techniques are proven to be very valuable, they are less successful to reach their goal if the process is flexible and, ...
- research-articleMarch 2020
Process discovery using in-database minimum self distance abstractions
SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied ComputingPages 26–35https://doi.org/10.1145/3341105.3373846Process executions generate event data that are typically stored in legacy information systems, such as databases. However, process discovery, which requires such event data, is performed in main memory. To bridge this gap, existing techniques must ...
- research-articleJanuary 2020
MOEA for discovering Pareto-optimal process models: an experimental comparison
International Journal of Computational Science and Engineering (IJCSE), Volume 21, Issue 3Pages 446–456https://doi.org/10.1504/ijcse.2020.106067Process mining aims at discovering the workflow of a process from the event logs that provide insights into organisational processes for improving these processes and their support systems. Process mining abstracts the complex real-life datasets into a ...
Process Mining to Unleash Variability Management: Discovering Configuration Workflows Using Logs
- Ángel Jesús Varela-Vaca,
- José A. Galindo,
- Belén Ramos-Gutiérrez,
- María Teresa Gómez-López,
- David Benavides
SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference - Volume APages 265–276https://doi.org/10.1145/3336294.3336303Variability models are used to build configurators. Configurators are programs that guide users through the configuration process to reach a desired configuration that fulfils user requirements. The same variability model can be used to design different ...
- editorialJanuary 2019
A practitioner’s guide to process mining: Limitations of the directly-follows graph
Procedia Computer Science (PROCS), Volume 164, Issue CPages 321–328https://doi.org/10.1016/j.procs.2019.12.189AbstractProcess mining techniques use event data to show what people, machines, and organizations are really doing. Process mining provides novel insights that can be used to identify and address performance and compliance problems. In recent years, the ...
- research-articleJuly 2018
Process mining and simulation: a match made in heaven!
SummerSim '18: Proceedings of the 50th Computer Simulation ConferenceArticle No.: 4, Pages 1–12Event data are collected everywhere: in logistics, manufacturing, finance, healthcare, e-learning, e-government, and many other domains. The events found in these domains typically refer to activities executed by resources at particular times and for ...
- posterJuly 2018
Discovering pareto-optimal process models: a comparison of MOEA techniques
GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 286–287https://doi.org/10.1145/3205651.3205657Process mining aims at discovering the workflow of a process from the event logs that provide insights into organizational processes for improving these processes and their support systems. Ideally a process mining algorithm should produce a model that ...
- research-articleMay 2018
Discovering process maps from event streams
ICSSP '18: Proceedings of the 2018 International Conference on Software and System ProcessPages 86–95https://doi.org/10.1145/3202710.3203154Automated process discovery is a class of process mining methods that allow analysts to extract business process models from event logs. Traditional process discovery methods extract process models from a snapshot of an event log stored in its entirety. ...
- research-articleApril 2017
Cyber-Physical System Discovery: Reverse Engineering Physical Processes
CPSS '17: Proceedings of the 3rd ACM Workshop on Cyber-Physical System SecurityPages 3–14https://doi.org/10.1145/3055186.3055195Successful cyber attacks against cyber-physical systems require expert knowledge about the dynamic behaviour of the underlying physical process. Therefore, obtaining the relevant information is a crucial part during attack preparation. Previous work has ...
- research-articleJanuary 2017
Incremental Process Discovery using Petri Net Synthesis
Process discovery aims at constructing a model from a set of observations given by execution traces (a log). Petri nets are a preferred target model in that they produce a compact description of the system by exhibiting its concurrency. This article ...
- research-articleJanuary 2017
Coupled Hidden Markov Model for Process Discovery of Non-Free Choice and Invisible Prime Tasks
Procedia Computer Science (PROCS), Volume 124, Issue CPages 134–141https://doi.org/10.1016/j.procs.2017.12.139AbstractWith increasing numbers and complexity of processes stored in the event log on a system, a solution to analyze these processes more easily is a formation of the process model. There are algorithms of process discovery that offered ways to formed ...
- articleDecember 2016
Comprehensible predictive models for business processes
Predictive modeling approaches in business process management provide a way to streamline operational business processes. For instance, they can warn decision makers about undesirable events that are likely to happen in the future, giving the decision ...
- articleSeptember 2016
The v-algorithm for discovering software process lines
Journal of Software: Evolution and Process (WSMR), Volume 28, Issue 9Pages 783–799https://doi.org/10.1002/smr.1778A software company can define a software process line SPrL to deal with projects with different characteristics. This entails defining a base process and its variation points; the SPrL is then tailored to each project. This approach avoids the co-...
- research-articleFebruary 2016
Synchronization-Core-Based Discovery of Processes with Decomposable Cyclic Dependencies
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 10, Issue 3Article No.: 31, Pages 1–29https://doi.org/10.1145/2845086Traditional process discovery techniques mine process models based upon event traces giving little consideration to workflow relevant data recorded in event logs. The neglect of such information usually leads to incorrect discovered models, especially ...
- research-articleSeptember 2015
Process mining in software systems: discovering real-life business transactions and process models from distributed systems
This paper presents a novel reverse engineering technique for obtaining real-life event logs from distributed systems. This allows us to analyze the operational processes of software systems under real-life conditions, and use process mining techniques ...