Computing and Information Systems - Research Publications

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    Robotic Process Mining
    Dumas, M ; Rosa, ML ; Leno, V ; Polyvyanyy, A ; Maggi, FM ; van der Aalst, WMP ; Carmona, J (Springer, Cham, 2022-06-27)
    User interaction logs allow us to analyze the execution of tasks in a business process at a finer level of granularity than event logs extracted from enterprise systems. The fine-grained nature of user interaction logs open up a number of use cases. For example, by analyzing such logs, we can identify best practices for executing a given task in a process, or we can elicit differences in performance between workers or between teams. Furthermore, user interaction logs allow us to discover repetitive and automatable routines that occur during the execution of one or more tasks in a process. Along this line, this chapter introduces a family of techniques, called Robotic Process Mining (RPM), which allow us to discover repetitive routines that can be automated using robotic process automation technology. The chapter presents a structured landscape of concepts and techniques for RPM, including techniques for user interaction log preprocessing, techniques for discovering frequent routines, notions of routine automatability, as well as techniques for synthesizing executable routine specifications for robotic process automation.
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    Data and Process Resonance: Identifier Soundness for Models of Information Systems
    van der Werf, JMEM ; Rivkin, A ; Polyvyanyy, A ; Montali, M (Springer International Publishing, 2022-01-01)
    A model of an information system describes its processes and how these processes manipulate data objects. Object-aware extensions of Petri nets focus on modeling the life-cycle of objects and their interactions. In this paper, we focus on Petri nets with identifiers, where identifiers are used to refer to objects. These objects should “behave” well in the system from inception to termination. We formalize this intuition in the notion of identifier soundness, and show that although this property is undecidable in general, useful subclasses exist that guarantee identifier soundness by construction.
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    Bootstrapping Generalization of Process Models Discovered from Event Data
    Polyvyanyy, A ; Moffat, A ; García-Bañuelos, L (Springer International Publishing, 2022-01-01)
    Process mining extracts value from the traces recorded in the event logs of IT-systems, with process discovery the task of inferring a process model for a log emitted by some unknown system. Generalization is one of the quality criteria applied to process models to quantify how well the model describes future executions of the system. Generalization is also perhaps the least understood of those criteria, with that lack primarily a consequence of it measuring properties over the entire future behavior of the system when the only available sample of behavior is that provided by the log. In this paper, we apply a bootstrap approach from computational statistics, allowing us to define an estimator of the model’s generalization based on the log it was discovered from. We show that standard process mining assumptions lead to a consistent estimator that makes fewer errors as the quality of the log increases. Experiments confirm the ability of the approach to support industry-scale data-driven systems engineering.
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    Process Querying: Methods, Techniques, and Applications
    Polyvyanyy, A ; Polyvyanyy, A (Springer International Publishing, 2022)
    Process querying studies concepts and methods from fields like Big data, process modeling and analysis, business process intelligence, and process analytics and applies them to retrieve and manipulate real-world and designed processes. This chapter reviews state-of-the-art methods for process querying, summarizes techniques used to implement process querying methods, discusses typical applications of process querying, and identifies research gaps and suggests directions for future research in process querying.
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    Process Query Language
    Polyvyanyy, A (Springer International Publishing, 2022)
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    Introduction to Process Querying
    Polyvyanyy, A (Springer International Publishing, 2022)
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    Early Detection and Classification of Patient-Ventilator Asynchrony Using Machine Learning
    Gao, E ; Ristanoski, G ; Aickelin, U ; Berlowitz, D ; Howard, M (Springer International Publishing, 2022-01-01)
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    Untangling the Concept of Artificial Intelligence, Machine Learning, and Deep Learning
    Juliandri, M ; Ristanoski, G ; Aickelin, U (Springer Nature Singapore, 2022)
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    Automating Digital Afterlives
    Fordyce, R ; Nansen, B ; Arnold, M ; Kohn, T ; Gibbs, M ; Jansson, A ; Adams, PC (Oxford University Press, 2021-08-26)
    The question of how the dead “live on” by maintaining a presence and connecting to the living within social networks has garnered the attention of users, entrepreneurs, platforms, and researchers alike. In this chapter we investigate the increasingly ambiguous terrain of posthumous connection and disconnection by focusing on a diverse set of practices implemented by users and offered by commercial services to plan for and manage social media communication, connection, and presence after life. Drawing on theories of self-presentation (Goffman) and technological forms of life (Lash), we argue that moderated and automated performances of posthumous digital presence cannot be understood as a continuation of personal identity or self-presentation. Rather, as forms of mediated human (after)life, posthumous social media presence materializes ambiguities of connection/disconnection and self/identity.
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    6. Silenced by Power: Repression, Isolation & Persecution
    Hale, D ; Dreyfus, S ; Colvin, N ; Myers, A ; Halgand-Mishra, D ; Brown, B (transcript Verlag, 2021-12-03)