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Mining Contextual Process Models Using Sensors Data: A Case of Daily Activities in Smart Home 19th

Mining Contextual Process Models Using Sensors Data: A Case ...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Elali, Ramona Kornyshova, Elena Deneckere, Rebecca Salinesi, Camille Paris 1 Pantheon Sorbonne Paris France Conservatoire Natl Arts & Metiers Paris France

ISBN: (纸本)9783031306938;9783031306945

Different techniques are used by companies to enhance their processes. Process mining (PM) is one of these techniques that relies on the user activity logs recorded by information systems to discover the process model, to check conformance with the prescribed process, to enhance the process, and to recommend or guess the next user activity. From another hand, many contextual factors such as time, location, weather, and user's profile influence the user activities. However, PM techniques are mainly activity-oriented and do not take into consideration the contextual environment. Our main goal is to enrich process models obtained using process mining technics with contextual information issued from sensors data and to construct contextual process models for a better process discovery, conformance checking, and recommendations. In this paper, we test the feasibility to integrate events logs with sensor logs to provide meaningful results. We use existing datasets with events and sensors logs about daily activities in Smart Home to construct a process model enriched by contextual information.

关键词： Process Mining Process Model Context Contextual Process Model Sensors Log Events Log Smart Home

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BERMUDA: Participatory Mapping of Domain Activities to Event Data via System Interfaces

BERMUDA: Participatory Mapping of Domain Activities to Event...

引用

4th International Conference on Process Mining (ICPM)

作者： Cosma, Vlad P. Hildebrandt, Thomas T. Gyldenkaerne, Christopher H. Slaats, Tijs Univ Copenhagen DK-2200 Copenhagen Denmark KMD ApS DK-2750 Ballerup Denmark Roskilde Univ Roskilde Denmark

ISBN: (纸本)9783031278143;9783031278150

We present a method and prototype tool supporting participatory mapping of domain activities to event data recorded in information systems via the system interfaces. The aim is to facilitate responsible secondary use of event data recorded in information systems, such as process mining and the construction of predictive AI models. Another identified possible benefit is the support for increasing the quality of data by using the mapping to support educating new users in how to register data, thereby increasing the consistency in how domain activities are recorded. We illustrate the method on two cases, one from a job center in a danish municipality and another from a danish hospital using the healthcare platform from Epic.

关键词： Data quality Secondary use Event extraction Event matching Participatory design

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Adaptive Task-Oriented Chatbots Using Feature-Based Knowledge Bases 1

引用

35th CAiSE Conference on Cyber-Human Systems

作者： Campas, Carla Motger, Quim Franch, Xavier Marco, Jordi Univ Politecn Cataluna Dept Serv & Informat Syst Engn Barcelona Spain Univ Politecn Cataluna Dept Comp Sci Barcelona Spain

ISBN: (数字)9783031346743

ISBN: (纸本)9783031346736;9783031346743

Task-oriented chatbots relying on a knowledge base for domain-specific content exploitation have been largely addressed in research and industry applications. Despite this, multiple challenges remain to be fully conquered, including adaptive knowledge mechanisms, personalization for user-specific demands, and composite intent resolution. To address these challenges, in this paper, we present a work-in-progress summary of a task-oriented, knowledge-based chatbot in the field of mobile software ecosystems. The chatbot is designed to assist users in the combined use of multiple features from different applications. The proposed knowledge base and the machine learning pipeline supporting the chatbot technical core are designed to: (i) effectively use user context, (ii) process runtime feedback, (iii) use user historical data, and (iv) automatically infer slot values and dependent actions. With this report, we expect to lay the groundwork for future development stages and user validation studies.

关键词： Natural Language Understanding Chatbots Mobile Feature Integration Adaptive Knowledge Bases

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A Goal-Driven Approach to Support Decision-Making with Incomplete information in Cyber Operations 1

引用

35th CAiSE Conference on Cyber-Human Systems

作者： Dawoud, Ahmed Mahala, Geeta Islam, Chadni Mayer, Wolfgang Ghose, Aditya Ali Babar, M. Stumptner, Markus Grossmann, Georg Univ South Australia Adelaide SA Australia Univ Wollongong Wollongong NSW Australia Univ Adelaide Adelaide SA Australia

ISBN: (数字)9783031346743

ISBN: (纸本)9783031346736;9783031346743

Semi-autonomous cyber security ("cyber") operations require effective communication between a human operator and the underlying cyber systems that carry out the mission. We show a goal-driven approach to specifying mission objectives of such systems, where the system has controlled autonomy to refine the goals into executable plans. An ontology aligns goal decomposition and data representation with human-level concepts, and probabilistic extensions of Belief-Desire-Intention (BDI) agent architectures allow dealing with uncertainty about the agent's state and the effects of its actions. Our framework effectively automates parts of cyber operations while conveying the state of operations to a human operator. A case study from the cyber operations domain demonstrates that this approach can outperform the traditional BDI agent approach while requiring minimal additional information by the agent programmer.

关键词： Decision making

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Local Energy Markets: A Market Transformation Survey Towards Segments of Interest 19th

Local Energy Markets: A Market Transformation Survey Towards...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Kapassa, Evgenia Touloupou, Marios Univ Nicosia Dept Digital Innovat Nicosia Cyprus

ISBN: (纸本)9783031306938;9783031306945

Given the rapid growth of distributed energy generation and the anticipated rise in demand-response, one of the most important issues is how to integrate the energy resources into the existing market. The energy sector has undergone a considerable transformation during the past years due to changing legislation, technologies and consumer behavior. Therefore, this work explores the patterns that form the energy market transformation, measures awareness regarding energy market and gain insights on energy market tools and services, through a survey implemented within the innovative project PARITY. Moreover, the knowledge gained from the participants is used to identify segments of interest. The main findings from the market transformation survey include among other topics, that the energy market is envisioned to be entirely based in DERs by the end of 2035, while the primary barrier for the latter are the lack of EU and national regulations, as well as the inadequate technological design, lack of standardization, and interoperability. The survey also revealed that smart energy contracts, load forecasting mechanisms, personalized profile models and dynamic pricing schemes are some of the services that can increase the productivity and profitability within local energy markets. Finally, this report is based on research carried out in early 2022, drawing from professionals within the H2020 project PARITY and were from a variety of industries with an emphasis on energy production, analysis, and consulting.

关键词： Local Energy Market Market Penetration Market Transformation Survey Segments of Interest

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Identifying the Steps in an Exploratory Data Analysis: A Process-Oriented Approach

Identifying the Steps in an Exploratory Data Analysis: A Pro...

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4th International Conference on Process Mining (ICPM)

作者： Van Daele, Seppe Janssenswillen, Gert UHasselt Hasselt Univ Fac Business Econ Agoralaan B-3590 Diepenbeek Belgium

ISBN: (纸本)9783031278143;9783031278150

Best practices in (teaching) data literacy, specifically Exploratory Data Analysis, remain an area of tacit knowledge until this day. However, with the increase in the amount of data and its importance in organisations, analysing data is becoming a much-needed skill in today's society. Within this paper, we describe an empirical experiment that was used to examine the steps taken during an exploratory data analysis, and the order in which these actions were taken. Twenty actions were identified. Participants followed a rather iterative process of working step by step towards the solution. In terms of the practices of novice and advanced data analysts, few relevant differences were yet discovered.

关键词： Process mining Deliberate practice Learning analytics

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Domain-Driven Event Abstraction Framework for Learning Dynamics in MOOCs Sessions

Domain-Driven Event Abstraction Framework for Learning Dynam...

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4th International Conference on Process Mining (ICPM)

作者： Hidalgo, Luciano Munoz-Gama, Jorge Pontificia Univ Catolica Chile Dept Comp Sci Santiago Chile

ISBN: (纸本)9783031278143;9783031278150

In conjunction with the rapid expansion of Massive Open Online Courses (MOOCs), academic interest has grown in the analysis of MOOC student study sessions. Education researchers have increasingly regarded process mining as a promising tool with which to answer simple questions, including the order in which resources are completed. However, its application to more complex questions about learning dynamics remains a challenge. For example, do MOOC students genuinely study from a resource or merely skim content to understand what will come next? One common practice is to use the resources directly as activities, resulting in spaghetti process models that subsequently undergo filtering. However, this leads to over-simplified and difficult-to-interpret conclusions. Consequently, an event abstraction becomes necessary, whereby low-level events are combined with high-level activities. A wide range of event abstraction techniques has been presented in process mining literature, primarily in relation to data-driven bottom-up strategies, where patterns are discovered from the data and later mapped to education concepts. Accordingly, this paper proposes a domain-driven top-down framework that allows educators who are less familiar with data and process analytics to more easily search for a set of predefined high-level concepts from their own MOOC data. The framework outlined herein has been successfully tested in a Coursera MOOC, with the objective of understanding the in-session behavioral dynamics of learners who successfully complete their respective courses.

关键词： Event abstraction MOOC Learning dynamics

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Cybersecurity and Data Quality in Cloud Computing: A Research Framework 19th

Cybersecurity and Data Quality in Cloud Computing: A Researc...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Xu, Hongjiang Butler Univ Sch Business 4600 Sunset Ave Indianapolis IN 46208 USA

ISBN: (纸本)9783031306938;9783031306945

In the cloud computing environment, cybersecurity and data quality capacities and vulnerabilities can have impact on could computing performance. Cloud computing resiliency addresses risks and capabilities in order to make cloud computing stronger and less susceptible to disruptions. Cloud computing provides many opportunities, however, it also presents some cybersecurity and data quality issues. In this paper, we propose a research framework for cybersecurity and data quality in the cloud computing environment.

关键词： Cybersecurity Cloud Computing Data Quality Risks Capabilities

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Modeling, Executing and Monitoring IoT-Driven business Rules 24th

Modeling, Executing and Monitoring IoT-Driven Business Rules

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24th International Working Conference on business Process Modeling, Development, and Support (BPMDS) / 28th International Working Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD)

作者： Kirikkayis, Yusuf Gallik, Florian Reichert, Manfred Ulm Univ Inst Databases & Informat Syst Ulm Germany

ISBN: (纸本)9783031342400;9783031342417

The Internet of Things (IoT) is used in various areas to ease daily life and to make it more efficient. The IoT is a network of physical objects equipped with sensors, actuators, software, and technologies for exchanging the gathered data. In numerous domains, such as healthcare and smart home, IoT devices can be used to enable smart applications. business Process Management (BPM), in turn, enables the analysis, modeling, implementation, execution, and monitoring of business processes. Extending BPM with IoT capabilities enhances process automation, improves process monitoring, and enables managing IoT-driven business rules. In the context of the latter the aggregation of low-level IoT data into high-level business information is a paramount important step. However, modeling, executing, and monitoring IoT-driven business rules based on BPMN 2.0 and Decision Model and Notation (DMN) might not be the best suited approach. This paper presents a framework that provides an extended BPMN notation for modeling, executing, and monitoring IoT-driven decision processes. The framework is implemented as a proof-of-concept prototype, a real-world scenario is presented to illustrate its use.

关键词： IoT Internet of Things business Rules business Rule Engine IoT-driven business Rules

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Detecting Complex Anomalous Behaviors in business Processes: A Multi-perspective Conformance Checking Approach

Detecting Complex Anomalous Behaviors in Business Processes:...

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4th International Conference on Process Mining (ICPM)

作者： Mehr, Azadeh Sadat Mozafari de Carvalho, Renata M. van Dongen, Boudewijn Eindhoven Univ Technol Dept Math & Comp Sci Eindhoven Netherlands

ISBN: (纸本)9783031278143;9783031278150

In recent years, organizations are putting an increasing emphasis on anomaly detection. Anomalies in business processes can be an indicator of system faults, inefficiencies, or even fraudulent activities. In this paper we introduce an approach for anomaly detection. Our approach considers different perspectives of a business process such as control flow, data and privacy aspects ***, it is able to detect complex anomalies in business processes like spurious data processing and misusage of authorizations. The approach has been implemented in the open source ProM framework and its applicability was evaluated through a real-life dataset from a financial organization. The experiment implies that in addition to detecting anomalies of each aspect, our approach can detect more complex anomalies which relate to multiple perspectives of a business process.

关键词： Outlier behavior detection Anomalous behavior Data privacy Conformance checking Multi-perspective analysis

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