List of Publications

@inproceedings{malburg_BPMResearch_2020,

title = {Using Physical Factory Simulation Models for Business Process Management Research},

author = {Lukas Malburg and Ronny Seiger and Ralph Bergmann and Barbara Weber},

editor = {Adela del-R\'{i}o-Ortega and Henrik Leopold and Flavia M. Santoro},

url = {http://www.wi2.uni-trier.de/shared/publications/2020_MalburgEtAl_BPM.pdf},

doi = {10.1007/978-3-030-66498-5_8},

year  = {2020},

date = {2020-01-01},

booktitle = {Business Process Management Workshops - BPM 2020 International Workshops, Sevilla, Spain, September 13 - 18, 2020},

volume = {397},

pages = {95\textendash107},

publisher = {Springer.},

series = {Lecture Notes in Business Information Processing},

abstract = {The production and manufacturing industries are currently transitioning towards more autonomous and intelligent production lines within the Fourth Industrial Revolution (Industry 4.0). Learning Factories as small scale physical models of real shop floors are realistic platforms to conduct research in the smart manufacturing area without depending on expensive real world production lines or completely simulated data. In this work, we propose to use learning factories for conducting research in the context of Business Process Management (BPM) and Internet of Things (IoT) as this combination promises to be mutually beneficial for both research areas. We introduce our physical Fischertechnik factory models simulating a complex production line and three exemplary use cases of combining BPM and IoT, namely the implementation of a BPM abstraction stack on top of a learning factory, the experience-based adaptation and optimization of manufacturing processes, and the stream processing-based conformance checking of IoT-enabled processes.},

note = {The original publication is available at www.springerlink.com},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{klein_ftonto_2019,

title = {FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies},

author = {Patrick Klein and Lukas Malburg and Ralph Bergmann},

editor = {Robert J\"{a}schke and Matthias Weidlich},

url = {http://www.wi2.uni-trier.de/shared/publications/2019_KleinMalburgBergmann_LWDA.pdf},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", Berlin, Germany, September 30 - October 2, 2019.},

volume = {2454},

pages = {253\textendash264},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

abstract = {Nowadays, semantic information provided by an ontology is indispensable in the context of Industry 4.0, especially when using methods from Artificial Intelligence. The currently available ontologies do not satisfy the demands of simulation environments used for research purposes. For this reason, we develop an ontology customized to Fischertechnik simulation factories by reusing existing ontologies. The ontology has been created according to requirements from two use cases. In our evaluation, it is determined that the ontology is suitable to represent machine components and their relationships while satisfying the specified requirements.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{bergmann_proCAKE_demo_2019,

title = {ProCAKE: A Process-Oriented Case-Based Reasoning Framework},

author = {Ralph Bergmann and Lisa Grumbach and Lukas Malburg and Christian Zeyen},

editor = {Stelios Kapetanakis and Hayley Borck},

url = {http://www.wi2.uni-trier.de/shared/publications/2019_BergmannGrumbachMalburgZeyen_ICCBR_Demo.pdf},

year  = {2019},

date = {2019-01-01},

booktitle = {Workshops Proceedings for the Twenty-seventh International Conference on Case-Based Reasoning co-located with the Twenty-seventh International Conference on Case-Based Reasoning (ICCBR 2019), Otzenhausen, Germany, September 8-12, 2019},

volume = {2567},

pages = {156\textendash161},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

abstract = {This paper presents ProCAKE \textendash the process-oriented case-based knowledge engine of the CAKE framework, which has evolved from several research projects at the University of Trier over the years. ProCAKE constitutes a domain-independent framework that can be used to implement diverse structural or process-oriented case-based reasoning applications for integrated process and knowledge management. This paper gives an overview of the main components and demonstrates their application by examples.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{klein_workflow_embedding_2019,

title = {Learning Workflow Embeddings to Improve the Performance of Similarity-Based Retrieval for Process-Oriented Case-Based Reasoning},

author = {Patrick Klein and Lukas Malburg and Ralph Bergmann},

editor = {Kerstin Bach and Cindy Marling},

url = {http://www.wi2.uni-trier.de/shared/publications/2019_KleinMalburgBergmann_ICCBR.pdf},

doi = {10.1007/978-3-030-29249-2_13},

year  = {2019},

date = {2019-01-01},

booktitle = {Case-Based Reasoning Research and Development: 27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8-12, 2019, Proceedings},

pages = {188\textendash203},

publisher = {Springer.},

series = {Lecture Notes in Computer Science},

abstract = {In process-oriented case-based reasoning, similarity-based retrieval of workflow cases from large case bases is still a difficult issue due to the computationally expensive similarity assessment. The two-phase MAC/FAC (“Many are called, but few are chosen") retrieval has been proven useful to reduce the retrieval time but comes at the cost of an additional modeling effort for implementing the MAC phase. In this paper, we present a new approach to implement the MAC phase for POCBR retrieval, which makes use of the StarSpace embedding algorithm to automatically learn a vector representation for workflows, which can be used to significantly speed-up the MAC retrieval phase. In an experimental evaluation in the domain of cooking workflows, we show that the presented approach outperforms two existing MAC/FAC approaches on the same data.},

note = {The original publication is available at www.springerlink.com},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zeyen_scientificWF_adaptation_2019,

title = {Adaptation of Scientific Workflows by Means of Process-Oriented Case-Based Reasoning},

author = {Christian Zeyen and Lukas Malburg and Ralph Bergmann},

editor = {Kerstin Bach and Cindy Marling},

url = {http://www.wi2.uni-trier.de/shared/publications/2019_ZeyenMalburgBergmann_ICCBR.pdf},

doi = {10.1007/978-3-030-29249-2_26},

year  = {2019},

date = {2019-01-01},

booktitle = {Case-Based Reasoning Research and Development: 27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8-12, 2019, Proceedings},

pages = {388\textendash403},

publisher = {Springer},

series = {Lecture Notes in Artificial Intelligence},

crossref = {DBLP:conf/iccbr/2019},

abstract = {This paper investigates automatic adaptation of scientific workflows in process-oriented case-based reasoning with the goal of providing modeling assistance. With regard to our previous work on the adaptation of business workflows, we discuss the differences between the workflow types and the implications for transferring the approaches to scientific workflows. An experimental evaluation with RapidMiner workflows demonstrates that the approaches can significantly improve workflows towards a given query while mostly maintaining their executability and semantic correctness.},

note = {The original publication is available at www.springerlink.com},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{malburg_workflow_reuse_2018,

title = {Query Model and Similarity-Based Retrieval for Workflow Reuse in the Digital Humanities},

author = {Lukas Malburg and Nicolas M\"{u}nster and Christian Zeyen and Ralph Bergmann},

editor = {Rainer Gemulla and Simone Paolo Ponzetto and Christian Bizer and Margret Keuper and Heiner Stuckenschmidt},

url = {http://www.wi2.uni-trier.de/publications/2018_MalburgMuensterZeyenBergmann_LWDA.pdf},

year  = {2018},

date = {2018-01-01},

booktitle = {Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", LWDA 2018},

volume = {2191},

pages = {251\textendash262},

publisher = {CEUR-WS.org},

abstract = {Scientific Workflows do not seem to be broadly used today in the Digital Humanities to perform text and data analysis. Although they have become established in e-Science, modeling new workflows is usually a demanding task, especially for novice users. Case-Based Reasoning (CBR) has been applied in the past to support the development of workflows as an experience-based activity by retrieving past workflows. A query language is needed for this purpose, but current languages do not sufficiently consider different user groups and the information they can provide. To address this issue, we present a query model to support novice as well as experienced users. We identify common expression elements from literature and integrate them in a prototypical CBR application named Reuse Assistant to support workflow reuse in the RapidMiner workflow tool. An experimental evaluation with non-expert users indicates the potential of the Reuse Assistant to facilitate workflow reuse and thus to simplify workflow development.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}