Bibliografías temáticas / Business Process Mining

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Literatura académica sobre el tema "Business Process Mining"

Autor: Grafiati
Publicado: 23 de noviembre de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Business Process Mining"

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Pourmasoumi, Asef, and Ebrahim Bagheri. "Business process mining." Encyclopedia with Semantic Computing and Robotic Intelligence 01, no. 01 (2017): 1630004. http://dx.doi.org/10.1142/s2425038416300044.

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One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining
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Kozlova, Elena. "Business process optimization with process mining." Drukerovskij Vestnik, no. 3 (June 23, 2025): 71–77. https://doi.org/10.17213/2312-6469-2025-3-71-77.

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van der Aalst, Wil. "Spreadsheets for business process management." Business Process Management Journal 24, no. 1 (2018): 105–27. http://dx.doi.org/10.1108/bpmj-10-2016-0190.

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Purpose Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers. Design/methodology/approach The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of pro
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Ingvaldsen, Jon Espen, and Jon Atle Gulla. "Model-Based Business Process Mining." Information Systems Management 23, no. 1 (2006): 19–31. http://dx.doi.org/10.1201/1078.10580530/45769.23.1.20061201/91769.3.

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Polpinij, Jantima, Aditya Ghose, and Hoa Khanh Dam. "Mining business rules from business process model repositories." Business Process Management Journal 21, no. 4 (2015): 820–36. http://dx.doi.org/10.1108/bpmj-01-2014-0004.

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Purpose – Business process has become the core assets of many organizations and it becomes increasing common for most medium to large organizations to have collections of hundreds or even thousands of business process models. The purpose of this paper is to explore an alternative dimension to process mining in which the objective is to extract process constraints (or business rules) as opposed to business process models. It also focusses on an alternative data set – process models as opposed to process instances (i.e. event logs). Design/methodology/approach – The authors present a new method
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Vasiliev, A. A., and A. V. Goryachev. "Applying Process Mining to Process Management." LETI Transactions on Electrical Engineering & Computer Science 16, no. 3 (2023): 52–59. http://dx.doi.org/10.32603/2071-8985-2023-16-3-52-59.

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Deals with the intellectual analysis of processes (Process Mining), which has recently gained popularity in various organizations. It is based on the construction of business process models in a specific area (for example, in the field of project management) based on event logs, providing a more accurate understanding of the actions occurring in business processes for the purpose of their subsequent analysis and improvement. The article defines process mining, event logs, lists the main tasks, algorithms and view models. The authors propose a methodology that can be used in the application of
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van der Aalst, W. M. P., H. A. Reijers, A. J. M. M. Weijters, et al. "Business process mining: An industrial application." Information Systems 32, no. 5 (2007): 713–32. http://dx.doi.org/10.1016/j.is.2006.05.003.

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Badakhshan, Peyman, Bastian Wurm, Thomas Grisold, Jerome Geyer-Klingeberg, Jan Mendling, and Jan vom Brocke. "Creating business value with process mining." Journal of Strategic Information Systems 31, no. 4 (2022): 101745. http://dx.doi.org/10.1016/j.jsis.2022.101745.

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Er, Mahendrawathi, Hanim Maria Astuti, and Dita Pramitasari. "Modeling and Analysis of Incoming Raw Materials Business Process: A Process Mining Approach." International Journal of Computer and Communication Engineering 4, no. 3 (2015): 196–203. http://dx.doi.org/10.17706/ijcce.2015.4.3.196-203.

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Himadeep, Movva. "Streamlining Process Discovery and Assessment with Process Mining and Task Mining." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 2 (2024): 1–9. https://doi.org/10.5281/zenodo.15087051.

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UiPath Task mining is an AI-powered feature that captures the user data performed on the desktop, records the granular level actions, including each mouse click and keystroke, and provides a visualization of the analyzed data captured with the help of Artificial Intelligence. Task Mining also helps users or business analysts identify the bottlenecks in the process and discrepancies and may even contribute to improving the process. This paper explores the usage and features of UiPath Task Mining. This research study also mentionsthe architecture overview of process mining, integrations, anddash
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Tesis sobre el tema "Business Process Mining"

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Nguyen, Hoang H. "Stage-aware business process mining." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/130602/9/Hoang%20Nguyen%20Thesis.pdf.

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Process mining enables the analysis of event logs to gain actionable insights into an organisation’s operations. However, state-of-the-art process mining techniques do not exploit the natural decomposition characteristics of business processes. “Process stages” are a generic type of business process decomposition prevalent in multiple domains, e.g. the stages of loan processing, the support levels in IT helpdesk, or the clinical stages in patient treatment. This study contributes a novel approach to process mining based on process stages. The approach is grounded on four techniques that allow
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Bala, Saimir, Macias Cristina Cabanillas, Andreas Solti, Jan Mendling, and Axel Polleres. "Mining Project- Oriented Business Processes." Springer, Cham, 2015. http://dx.doi.org/10.1007/978-3-319-23063-4_28.

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Large engineering processes need to be monitored in detail regarding when what was done in order to prove compliance with rules and regulations. A typical problem of these processes is the lack of con- trol that a central process engine provides, such that it is difficult to track the actual course of work even if data is stored in version control systems (VCS). In this paper, we address this problem by defining a mining technique that helps to generate models that visualize the work history as GANTT charts. To this end, we formally define the notion of a project-oriented business proc
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Turner, Christopher James. "A genetic programming based business process mining approach." Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4471.

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As business processes become ever more complex there is a need for companies to understand the processes they already have in place. To undertake this manually would be time consuming. The practice of process mining attempts to automatically construct the correct representation of a process based on a set of process execution logs. The aim of this research is to develop a genetic programming based approach for business process mining. The focus of this research is on automated/semi automated business processes within the service industry (by semi automated it is meant that part of the process
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Burattin, Andrea <1984&gt. "Applicability of Process Mining Techniques in Business Environments." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5446/1/thesis-final-v4.pdf.

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This thesis analyses problems related to the applicability, in business environments, of Process Mining tools and techniques. The first contribution is a presentation of the state of the art of Process Mining and a characterization of companies, in terms of their "process awareness". The work continues identifying circumstance where problems can emerge: data preparation; actual mining; and results interpretation. Other problems are the configuration of parameters by not-expert users and computational complexity. We concentrate on two possible scenarios: "batch" and "on-line" Process Mini
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Burattin, Andrea <1984&gt. "Applicability of Process Mining Techniques in Business Environments." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5446/.

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This thesis analyses problems related to the applicability, in business environments, of Process Mining tools and techniques. The first contribution is a presentation of the state of the art of Process Mining and a characterization of companies, in terms of their "process awareness". The work continues identifying circumstance where problems can emerge: data preparation; actual mining; and results interpretation. Other problems are the configuration of parameters by not-expert users and computational complexity. We concentrate on two possible scenarios: "batch" and "on-line" Process Mini
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Al, Jlailaty Diana. "Mining Business Process Information from Emails Logs for Process Models Discovery." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLED028.

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Les informations échangées dans les textes des courriels sont généralement concernées par des événements complexes ou des processus métier dans lesquels les entités qui échangent des courriels collaborent pour atteindre les objectifs finaux des processus. Ainsi, le flux d’informations dans les courriels envoyés et reçus constitue une partie essentielle, les activités métier de l’entreprise. L’extraction d’informations sur les processus métier à partir des courriels peut aider à améliorer la gestion des courriels pour les utilisateurs. Il peut également être utilisé pour tr
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Ostovar, Alireza. "Business process drift: Detection and characterization." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/127157/1/Alireza_Ostovar_Thesis.pdf.

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This research contributes a set of techniques for the early detection and characterization of process drifts, i.e. statistically significant changes in the behavior of business operations, as recorded in transactional data. Early detection and subsequent characterization of process drifts allows organizations to take prompt remedial actions and avoid potential repercussions resulting from unplanned changes in the behavior of their operations.
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Yongsiriwit, Karn. "Modeling and mining business process variants in cloud environments." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL002/document.

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De plus en plus les organisations adoptent les systèmes d'informations sensibles aux processus basés sur Cloud en tant qu'un environnement pour gérer et exécuter des processus dans le Cloud dans l'objectif de partager et de déployer leurs applications de manière optimale. Cela est particulièrement vrai pour les grandes organisations ayant des succursales opérant dans des différentes régions avec des processus considérablement similaires. Telles organisations doivent soutenir de nombreuses variantes du même processus en raison de la culture locale de leurs succursales, de leurs règlements, etc.
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Yongsiriwit, Karn. "Modeling and mining business process variants in cloud environments." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL002.

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De plus en plus les organisations adoptent les systèmes d'informations sensibles aux processus basés sur Cloud en tant qu'un environnement pour gérer et exécuter des processus dans le Cloud dans l'objectif de partager et de déployer leurs applications de manière optimale. Cela est particulièrement vrai pour les grandes organisations ayant des succursales opérant dans des différentes régions avec des processus considérablement similaires. Telles organisations doivent soutenir de nombreuses variantes du même processus en raison de la culture locale de leurs succursales, de leurs règlements, etc.
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Bou, nader Ralph. "Enhancing email management efficiency : A business process mining approach." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAS017.

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La gestion des processus métier (BPM) est cruciale pour toute organisation cherchant à améliorer constamment ses opérations. Cela implique plusieurs étapes : conception, modélisation, exécution, surveillance, optimisation et automatisation. Un élément central du BPM est l'analyse des processus, qui consiste à examiner les traces d'exécution pour identifier les inefficacités et les déviations par rapport aux processus prévus. Cette analyse se concentre particulièrement sur la prédiction des processus futurs et sur la vérification de leur conformité. Dans cette thèse, nous nous penchons sur les
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Libros sobre el tema "Business Process Mining"

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Burattin, Andrea. Process Mining Techniques in Business Environments. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17482-2.

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service), SpringerLink (Online, ed. Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer-Verlag Berlin Heidelberg, 2011.

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Piattini, Mario, and Ricardo Perez-Castillo. Uncovering essential software artifacts through business process archeology. Business Science Reference, an imprint of IGI Global, 2014.

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Buchwald, Hagen. S-BPM ONE – Setting the Stage for Subject-Oriented Business Process Management: First International Workshop, Karlsruhe, Germany, October 22, 2009. Revised Selected Papers. Springer-Verlag Heidelberg, 2010.

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Kumar, Akhil. Business Process Management. Taylor & Francis Group, 2018.

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Business Process Management. Routledge, 2018.

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Business Process Management. Taylor & Francis Group, 2018.

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Kumar, Akhil. Business Process Management. Taylor & Francis Group, 2018.

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Burattin, Andrea. Process Mining Techniques in Business Environments: Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining. Springer, 2015.

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Burattin, Andrea. Process Mining Techniques in Business Environments: Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining. Springer, 2015.

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Capítulos de libros sobre el tema "Business Process Mining"

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Burattin, Andrea. "Process Mining." In Process Mining Techniques in Business Environments. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17482-2_5.

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Leemans, Sander J. J. "Process Mining." In Lecture Notes in Business Information Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96655-3_3.

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van der Aalst, Wil, Arya Adriansyah, Ana Karla Alves de Medeiros, et al. "Process Mining Manifesto." In Business Process Management Workshops. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28108-2_19.

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Folino, Francesco, and Luigi Pontieri. "Business Process Deviance Mining." In Encyclopedia of Big Data Technologies. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63962-8_100-1.

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Folino, Francesco, and Luigi Pontieri. "Business Process Deviance Mining." In Encyclopedia of Big Data Technologies. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-77525-8_100.

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Buffett, Scott, and Bruce Hamilton. "Abductive Workflow Mining." In Business Process Management Workshops. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00328-8_15.

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Syed, Rehan, Sander J. J. Leemans, Rebekah Eden, and Joos A. C. M. Buijs. "Process Mining Adoption." In Lecture Notes in Business Information Processing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58638-6_14.

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Mannhardt, Felix. "Responsible Process Mining." In Lecture Notes in Business Information Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08848-3_12.

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AbstractThe prospect of data misuse negatively affecting our life has lead to the concept of responsible data science. It advocates for responsibility to be built, by design, into data management, data analysis, and algorithmic decision making techniques such that it is made difficult or even impossible to intentionally or unintentionally cause harm. Process mining techniques are no exception to this and may be misused and lead to harm. Decisions based on process mining may lead to unfair decisions causing harm to people by amplifying the biases encoded in the data by disregarding infrequently
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Dumas, Marlon, Marcello La Rosa, Volodymyr Leno, Artem Polyvyanyy, and Fabrizio Maria Maggi. "Robotic Process Mining." In Lecture Notes in Business Information Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08848-3_16.

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AbstractUser 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 proce
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Burattin, Andrea. "Streaming Process Mining." In Lecture Notes in Business Information Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08848-3_11.

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AbstractStreaming process mining refers to the set of techniques and tools which have the goal of processing a stream of data (as opposed to a finite event log). The goal of these techniques, similarly to their corresponding counterparts described in the previous chapters, is to extract relevant information concerning the running processes. This chapter presents an overview of the problems related to the processing of streams, as well as a categorization of the existing solutions. Details about control-flow discovery and conformance checking techniques are also presented together with a brief
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Actas de conferencias sobre el tema "Business Process Mining"

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Gavric, Aleksandar, Dominik Bork, and Henderik Proper. "Multimodal Process Mining." In 2024 26th International Conference on Business Informatics (CBI). IEEE, 2024. https://doi.org/10.1109/cbi62504.2024.00021.

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Aa, Han van der, Claudio Di Ciccio, Djordje Djurica, et al. "Process Mining and Visual Analytics." In 2024 26th International Conference on Business Informatics (CBI). IEEE, 2024. https://doi.org/10.1109/cbi62504.2024.00039.

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López-Pintado, Orlenys, Serhii Murashko, and Marlon Dumas. "Discovery and Simulation of Data-Aware Business Processes." In 2024 6th International Conference on Process Mining (ICPM). IEEE, 2024. http://dx.doi.org/10.1109/icpm63005.2024.10680675.

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Kirchdorfer, Lukas, Robert Blümel, Timotheus Kampik, Han Van der Aa, and Heiner Stuckenschmidt. "AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation." In 2024 6th International Conference on Process Mining (ICPM). IEEE, 2024. http://dx.doi.org/10.1109/icpm63005.2024.10680660.

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Pasquadibisceglie, Vincenzo, Annalisa Appice, and Donato Malerba. "LUPIN: A LLM Approach for Activity Suffix Prediction in Business Process Event Logs." In 2024 6th International Conference on Process Mining (ICPM). IEEE, 2024. http://dx.doi.org/10.1109/icpm63005.2024.10680620.

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Wuyts, Brecht, Seppe Vanden Broucke, and Jochen De Weerdt. "SuTraN: an Encoder-Decoder Transformer for Full-Context-Aware Suffix Prediction of Business Processes." In 2024 6th International Conference on Process Mining (ICPM). IEEE, 2024. http://dx.doi.org/10.1109/icpm63005.2024.10680671.

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Zaidi, Taskeen, Shivam Khurana, Kunal Sharma, S. Jayasree, Rupali A. Mahajan, and Megha Pandey. "Evaluating the Usefulness of Data Mining for Business Process Automation." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10723900.

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Hildebrandt, Tobias, and Lars Mehnen. "Cross-course Process Mining of Student Clickstream Data - Aggregation and Group Comparison." In 2024 26th International Conference on Business Informatics (CBI). IEEE, 2024. https://doi.org/10.1109/cbi62504.2024.00020.

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Chinces, Diana, and Ioan Salomie. "Business process mining algorithms." In 2013 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2013. http://dx.doi.org/10.1109/iccp.2013.6646120.

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Esfahani, Faramarz Safi, Masrah Azrifah Azmi Murad, Md Nasir Sulaiman, and Nur Izura Udzir. "Using process mining to business process distribution." In the 2009 ACM symposium. ACM Press, 2009. http://dx.doi.org/10.1145/1529282.1529755.

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Informes sobre el tema "Business Process Mining"

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Бакум, З. П., and В. В. Ткачук. Mining Engineers Training in Context of Innovative System of Ukraine. Криворізький державний педагогічний університет, 2014. http://dx.doi.org/10.31812/0564/425.

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The paper clarifies the process of a mining engineer training in terms of the innovation system of Ukraine. The authors analyze a number of normative documents concerning innovative activity in Ukraine in general and mining business in particular. In the process of implementation of innovations into mining industrial complex urgent problems are defined. The methodology of information and communication technologies (electronic, distance and mobile studies) usage in engineers training within the conditions of university education is offered. It is marked that the worked out methodology finds its
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Volkova, Nataliia P., Nina O. Rizun, and Maryna V. Nehrey. Data science: opportunities to transform education. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3241.

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The article concerns the issue of data science tools implementation, including the text mining and natural language processing algorithms for increasing the value of high education for development modern and technologically flexible society. Data science is the field of study that involves tools, algorithms, and knowledge of math and statistics to discover knowledge from the raw data. Data science is developing fast and penetrating all spheres of life. More people understand the importance of the science of data and the need for implementation in everyday life. Data science is used in business
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Bernal, Richard L. Chinese Foreign Direct Investment in the Caribbean: Potential and Prospects. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0009313.

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China has recently become the third largest source of foreign direct investment (FDI) in the world and is a major source of development aid for developing countries, including those in the Caribbean. The capital flows it provides have taken the form of loans to governments to finance infrastructure projects and to expand production of oil and other raw materials. There have been indications of interest in further investment in the Caribbean from Chinese enterprises and entrepreneurs. This is driven by both state policy, which seeks to more actively integrate China into the global economy, and
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Cimene, Dr Francis Thaise A. Emerging Technological Trends and Business Process Management: Preparing the Philippines for the Future. Asian Productivity Organization, 2024. https://doi.org/10.61145/dktv2301.

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The Philippine IT-BPM sector plays a vital role in driving economic growth and global competitiveness. This mini-report highlights how emerging technologies such as cloud computing, IoT, and big data analytics are transforming traditional business processes. Grounded in endogenous growth theory, the report emphasizes the impact of innovation and human capital on productivity. Policy recommendations are provided to bolster the nation’s position as a leading outsourcing hub and prepare for future technological advancements.
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Price, Roz. Taxation and Public Financial Management of Mining Revenue in the Democratic Republic of Congo. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.144.

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This rapid review provides a summary of the evidence on the taxation and public financial management of mining revenues in the Democratic Republic of Congo (DRC). This is a very complex topic, with a large and growing literature base, a huge interest by donors, non-governmental organisations and businesses, with some conflicting information at times. In particular, specific data on provincial budgets and spending was not identified during this review. No specific information on public financial management in either of these provinces was identified during the course of this review. Given the b
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Kornelakis, Andreas, Chiara Benassi, Damian Grimshaw, and Marcela Miozzo. Robots at the Gates? Robotic Process Automation, Skills and Institutions in Knowledge-Intensive Business Services. Digital Futures at Work Research Centre, 2022. http://dx.doi.org/10.20919/vunu3389.

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Against the backdrop of the fourth industrial revolution, this paper examines the emergence of Robotic Process Automation (RPA) as one of the new technologies that are shaping the future of work and reconfiguring sectoral business and innovation systems and models. It discusses how the institutional context can potentially mediate the digital transformation of services, how RPA affects workers’ employment and skills, and how it alters inter-organisational relationships and capabilities. Bringing together different strands of academic literature on employment studies, innovation, and technology
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Pueyo, Ana, Gisela Ngoo, Editruda Daulinge, and Adriana Fajardo. The Quest for Scalable Business Models for Mini-Grids in Africa: Implementing the Keymaker Model in Tanzania. Institute of Development Studies, 2022. http://dx.doi.org/10.19088/ids.2022.071.

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Achieving universal electrification in sub-Saharan Africa requires creative solutions. Renewable mini-grids are a promising technology to electrify remote communities with a substantial productive demand, mainly from agro-processing. Mini-grids have experienced fast growth and there are now around 2,200 systems in the sub-Saharan Africa region. However, their economic case in the sub-continent is unclear. Most mini-grids are struggling not only to obtain a profit but also to recover costs. This Research Report describes the case of a private company in Tanzania implementing a business model fo
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Olsson, Olle. Industrial decarbonization done right: identifying success factors for well-functioning permitting processes. Stockholm Environment Institute, 2021. http://dx.doi.org/10.51414/sei2021.034.

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1 Introduction 1.1 The urgency of industrial decarbonization The last few years have seen several of the world’s largest carbon dioxide-emitting countries and leading heavy industry companies committing to mid-century net-zero targets (Buckley 2021; Denyer and Kashiwagi 2020; McCurry 2020; Myers 2020). Consequently, the discussion on economy-wide transition to net-zero is accelerating, with focus shifting from “if” to “when” and “how”, even for heavy industry sectors like steel, cement and chemicals. This makes it increasingly urgent to analyse not just whether it is technologically feasible t
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Hutchinson, M. L., J. E. L. Corry, and R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.

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For meat and meat products, secondary processes are those that relate to the downstream of the primary chilling of carcasses. Secondary processes include maturation chilling, deboning, portioning, mincing and other operations such as thermal processing (cooking) that create fresh meat, meat preparations and ready-to-eat meat products. This review systematically identified and summarised information relating to antimicrobial resistance (AMR) during the manufacture of secondary processed meatand meat products (SPMMP). Systematic searching of eight literature databases was undertaken and the resu
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Guevara-Castañeda, Diego Alejandro, Leonardo Villar-Gómez, Olga Lucía Acosta-Navarro, et al. Report of the Board of Directors to the Congress of Colombia, February 2025. Banco de la República, 2025. https://doi.org/10.32468/inf-jun-dir-con-rep-eng.01-2025.

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In 2024, the macroeconomic adjustment process continued, characterized by a sustained reduction in inflation that began in 2023 and a decline in the current account deficit of the balance of payments. This adjustment took place in the context of a contractionary monetary policy, with a gradual reduction in the monetary policy interest rate. GDP grew by 1.7%, driven by investment and consumption, while employment increased by 2.2%. Foreign reserves remained at adequate levels, and Banco de la República recorded a profit of COP 10,041 billion, benefiting from the returns on foreign reserves. Mac
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