Related papers: Ontology-Based Process Modelling -- Will we live t…
The definition and representation of planning problems is at the heart of AI planning research. A key part is the representation of action models. Decades of advances improving declarative action model representations resulted in numerous…
Existing well investigated Predictive Process Monitoring techniques typically construct a predictive model based on past process executions, and then use it to predict the future of new ongoing cases, without the possibility of updating it…
This paper presents an ontology-based approach for the design of a collaborative business process model (CBP). This CBP is considered as a specification of needs in order to build a collaboration information system (CIS) for a network of…
Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are…
Vehicles in public traffic that are equipped with Automated Driving Systems are subject to a number of expectations: Among other aspects, their behavior should be safe, conforming to the rules of the road and provide mobility to their…
Students of software engineering struggle to develop a systems perspective because most of the software engineering methodologies focus on developing a particular aspect of a system. Lack of unified coverage to the topic of systems…
The observation of the nature and world represents the main source of human knowledge on the basis of our reason. At the present it is also the use of precise measurement approaches, which may contribute significantly to the knowledge of…
Explainability is motivated by the lack of transparency of black-box Machine Learning approaches, which do not foster trust and acceptance of Machine Learning algorithms. This also happens in the Predictive Process Monitoring field, where…
Business process simulation (BPS) is a key tool for analyzing and optimizing organizational workflows, supporting decision-making by estimating the impact of process changes. The reliability of such estimates depends on the ability of a BPS…
The Multilingual Semantic Web has been in focus for over a decade. Multilingualism in Linked Data and RDF has shown substantial adoption, but this is unclear for ontologies since the last review 15 years ago. One of the design goals for OWL…
Production machine learning (ML) systems fail silently -- not with crashes, but through wrong decisions. While observability is recognized as critical for ML operations, there is a lack empirical evidence of what practitioners actually…
Interpretable machine learning tackles the important problem that humans cannot understand the behaviors of complex machine learning models and how these models arrive at a particular decision. Although many approaches have been proposed, a…
The growth in variety and volume of OLTP (Online Transaction Processing) applications poses a challenge to OLTP systems to meet performance and cost demands in the existing hardware landscape. These applications are highly interactive…
In this research paper we address the importance of Product Data Management (PDM) with respect to its contributions in industry. Moreover we also present some currently available major challenges to PDM communities and targeting some of…
While classical planning languages make the closed-domain and closed-world assumption, there have been various approaches to extend those with DL reasoning, which is then interpreted under the usual open-world semantics. Current approaches…
Internship assignment is a complicated process for universities since it is necessary to take into account a multiplicity of variables to establish a compromise between companies' requirements and student competencies acquired during the…
There is an ongoing debate in computer science how algorithms should best be studied. Some scholars have argued that experimental evaluations should be conducted, others emphasize the benefits of formal analysis. We believe that this debate…
Mathematical models are increasingly used in both academia and the pharmaceutical industry to understand how phenotypes emerge from systems of molecular interactions. However, their current construction as monolithic sets of equations…
In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The…
Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these…