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检索条件"丛书名=Lecture Notes in Business Information Processing 252"

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Negotiation Platform for Supporting Multi-issue Bilateral Negotiations: The Case of an Offshore Wind Energy Company and a Fishing Community in the Northeast of Brazil 24th

Negotiation Platform for Supporting Multi-issue Bilateral Ne...

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24th International Conference on Group Decision and Negotiation (GDN)

作者： Frej, Eduarda Asfora da Silva, Gabriela Silva da Silva, Maria Luiza Morais, Danielle Costa Univ Fed Pernambuco UFPE CDSID Ctr Decis Syst & Informat Dev Av Acad Helio Ramos S-NCidade Univ BR-50740530 Recife PE Brazil

ISBN: (纸本)9783031593727;9783031593734

This paper presents the development of an electronic negotiation platform to support multi-issue bilateral negotiation situations. The proposed platform has an embedded module for preferences elicitation based on the FITradeoff multicriteria method, to support negotiators with the evaluation of candidate packages when proposing offers or when deciding whether to accept or not an offer from its counterpart. The design and structure of the platform are described in detail in this paper. In order to illustrate the applicability of the proposed platform, a negotiation problem concerning the use of maritime areas in the Northeast region of Brazil is presented. The results of a negotiation between an OffshoreWind Turbine (OWT) company and a Fishing community is presented, in which conflicts with respect to four issues were dealt and a total of 256 packages were involved. After 7 negotiation rounds, an agreement was reached, and a post-settlement analysis was performed to verify the efficiency of the agreement package.

关键词： Negotiation Support Electronic Platform Preferences Elicitation Software architecture FITradeoff method

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A Preliminary Analysis of the Adoption of Intelligent information Systems in Colombia 25th

A Preliminary Analysis of the Adoption of Intelligent Inform...

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25th International Conference on Enterprise information Systems (ICEIS)

作者： Abadia, Sofia Avila, Oscar Univ los Andes Sch Engn Dept Syst & Comp Engn Bogota Colombia

ISBN: (纸本)9783031647475;9783031647482

The integration of Enterprise information Systems (EIS) with data analytics tools has generated new systems known as Intelligent EIS which have opened up the way for more efficient data management and decision-making processes. It is not always easy for an organization to adopt new systems and/or technologies despite their advantages, as there are influencing factors that facilitate or difficult their adoption. When reviewing the literature, we found some international works that aim to identify adoption factors for this type of information systems. However, no work was found on this topic for the Colombian context. Consequently, this article aims at identifying the relevant factors for the adoption of intelligent EIS by comparing the results of the revision of an international literature with the results of a focus group of 5 industry experts in Colombia. As a preliminary result, we found that in the Colombian industry the most important influencing factors include cost and IT capabilities which differs from main factors identified in the revision of the international scholar literature.

关键词： Intelligent information systems Data analytics Adoption Influencing factors Smart information system

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Predictive Monitoring of business Process Execution Delays 6th

Predictive Monitoring of Business Process Execution Delays

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6th International Conference on information and Knowledge Systems (ICIKS)

作者： Ben Fradj, Walid Turki, Mohamed Univ Sfax MIRACL Lab ISIMS POB 242 Sfax 3021 Tunisia

ISBN: (纸本)9783031516634;9783031516641

Nowadays, organizations are becoming increasingly aware of the importance of better utilizing their knowledge assets and adopting a quality management model based on a process approach. This can be achieved by adopting a multidisciplinary approach that combines the fields of Knowledge Management, business Process Management and Process Mining. Therefore, to improve their performance and increase their responsiveness, organizations must identify, manage and monitor all the business processes (BP) that are likely to mobilize crucial knowledge. In fact, implementing an IT system that automates business processes is necessary to achieve these goals. In this context, we propose a new method for predicting the execution times of business processes baptized BPETPM. This method is based on the CRISP-DM approach. We used a Process Mining techniques particularly the machine learning to exploit the execution data of a workflow engine. In order to prove the applicability of this method we have developed an intelligent system for predicting execution time of BP named iBPMS4PET. The applicative framework of this research work is the incoming mail management process as part of a group health insurance.

关键词： business Process Management Process Mining Knowledge Management Machine Learning CRISP-DM

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Blockchain Evolution and Its Impact on business Models: A Comprehensive Review 25th

Blockchain Evolution and Its Impact on Business Models: A Co...

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25th International Conference on Enterprise information Systems (ICEIS)

作者： Vella, Giacomo Ghezzi, Davide Gastaldi, Luca Ghezzi, Antonio Politecn Milan Milan Italy

ISBN: (纸本)9783031647543;9783031647550

Blockchain technology, originally conceived as the foundational technology of Bitcoin in 2008, has transcended its initial role and now holds transformative potential beyond cryptocurrencies. Despite the significant potential changes that blockchain could bring to business and management, current research predominantly centers on technological aspects and practical applications. Both academics and practitioners continue to grapple with a clear understanding of blockchain's potential impacts. Moreover, the existing scientific literature addressing the business adoption of blockchain seems to overlook the increasing differentiation of real-world blockchain applications. This study aims to address this gap by systematically investigating the existing body of knowledge through a comprehensive review. In this review, we present the potential impacts of blockchain on business models and outline future research avenues. The analysis is based on 74 scientific articles published between January 2008 and July 2023. The review is structured around two frameworks: the elements of value creation, delivery, and capture within business models, and the various stages of blockchain application evolution. The findings underscore the necessity for a more nuanced exploration of real-world blockchain applications and their multifaceted effects on business models. This study contributes to the evolving discourse on the managerial and organizational dimensions of blockchain and offers insights for future research directions in this evolving field.

关键词： Blockchain business model Value creation Value delivery Value capture

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Expanding the Capacities of a CNN-Based Ant Counting and Density Estimation Application 25th

Expanding the Capacities of a CNN-Based Ant Counting and Den...

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25th International Conference on Enterprise information Systems (ICEIS)

作者： Silva, Mateus Coelho Felisberto, Breno Henrique Batista, Mateus Caldeira Bianchi, Andrea Gomes Campos Ribeiro, Servio Pontes Oliveira, Ricardo Augusto Rabelo Univ Fed Ouro Preto Comp Dept Ouro Preto Brazil Univ Fed Vicosa Gen Biol Dept Vicosa MG Brazil Univ Fed Ouro Preto Biol Dept Ouro Preto Brazil

ISBN: (纸本)9783031647475;9783031647482

Understanding collective insect behaviour is a pertinent ecological problem that has to be solved. The fact that some of these flocks are the largest cooperative units in nature has a tremendous impact on our knowledge of nature. Reliable data sampling contributes to the challenge's complexity in some ways. Based on convolutional neural networks, this paper proposes a novel technique for comprehending the numbers and distribution of ants in colonies. Due to the special nature of this tool, we developed an application to generate the marked dataset, produced the initial dataset, and evaluated the solution using several backbones. Our findings imply that the suggested strategy is workable to address the suggested problem. The average coefficient of determination R-2 with the ground truth counting was 0.9783 using the MobileNet as the backbone and 0.9792 using the EfficientNet-V2B0 as the backbone. The global average for the semi-quantitive classification of each image region was 86% for the MobileNet and 88% for the EfficientNet V2-B0. There was no statistically significant difference between both cases' average and median errors. The coefficient of determination was close to the statistical significance threshold (p = 0.065). The application using the MobileNet as its backbone performed the task faster than the version using the EfficientNet V2-B0, with statistical significance (p < 0.05).

关键词： Convolutional neural networks Ant ecology Population estimation

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TimeFlows: Visualizing Process Chronologies from Vast Collections of Heterogeneous information Objects 18th

TimeFlows: Visualizing Process Chronologies from Vast Collec...

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Muller, Max Lonysa Saaman, Erik van der Werf, Jan Martijn E. M. Jeurgens, Charles Reijers, Hajo A. Nationaal Archief The Hague Netherlands Univ Utrecht Utrecht Netherlands Univ Amsterdam Amsterdam Netherlands

ISBN: (纸本)9783031594649;9783031594656

In many fact-finding investigations, notably parliamentary inquiries, process chronologies are created to reconstruct how a controversial policy or decision came into existence. Current approaches, like timelines, lack the expressiveness to represent the variety of relations in which historic events may link to the overall chronology. This obfuscates the nature of the interdependence among the events, and the texts from which they are distilled. Based on explorative interviews with expert analysts, we propose an extended, rich set of relationships. We describe how these can be visualized as TimeFlows. We provide an example of such a visualization by illustrating the Childcare Benefits Scandal - an affair that deeply affected Dutch politics in recent years. This work extends the scope of existing process discovery research into the direction of unveiling non-repetitive processes from unstructured information objects.

关键词： Timeline Process Chronology TimeFlow Parliamentary Inquiry

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Investigating an Ontology-Informed Approach to Event Log Generation in Healthcare 5th

Investigating an Ontology-Informed Approach to Event Log Gen...

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5th International Conference on Process Mining (ICPM)

作者： Dwyer, Owen P. Chammas, Lara Sallinger, Emanuel Davies, Jim Univ Oxford Oxford England TU Wien Vienna Austria

ISBN: (纸本)9783031561061;9783031561078

Process mining methods have the potential to reveal useful patterns in hospital data and provide insights into patterns of treatment, but healthcare has proven an exceptionally challenging domain due to the significant heterogeneity of possible events and the diversity of individual patients. When studying a patient's pathway, their history might contain hundreds of events unrelated to the disease of interest;determining which to include or exclude in an event log is difficult, and highly dependent on the situation. Typically, researchers only include the most common or correlated events (risking missing rare but significant exceptions), or hand-curate a list of events (slow and difficult, especially where there might be thousands of possible events). We discuss an alternative approach that uses logical reasoning over ontologies to deduce plausibly related events, which might have implications in terms of time savings, the facilitation of reproducible research, and the enabling of comparisons across datasets and healthcare systems. We investigate the practical feasibility of such an approach by demonstrating it on real data, finding that the discovered processes approximate those produced through established approaches, with some caveats. The approach is a promising way to support conversations with domain experts and expedite human processes, and highlights the potential of structured domain knowledge to inform and enhance the event log generation process.

关键词： preprocessing filtering ontologies

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Enhancing the Accuracy of Predictors of Activity Sequences of business Processes 1

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Ali, Muhammad Awais Dumas, Marlon Milani, Fredrik Univ Tartu Tartu Estonia

ISBN: (数字)9783031594656

ISBN: (纸本)9783031594649;9783031594656

Predictive process monitoring is an evolving research field that studies how to train and use predictive models for operational decision-making. One of the problems studied in this field is that of predicting the sequence of upcoming activities in a case up to its completion, a.k.a. the case suffix. The prediction of case suffixes provides input to estimate short-term workloads and execution times under different resource schedules. Existing methods to address this problem often generate suffixes wherein some activities are repeated many times, whereas this pattern is not observed in the data. Closer examination shows that this shortcoming stems from the approach used to sample the successive activity instances to generate a case suffix. Accordingly, the paper introduces a sampling approach aimed at reducing repetitions of activities in the predicted case suffixes. The approach, namely Daemon Action, strikes a balance between exploration and exploitation when generating the successive activity instances. We enhance a deep learning approach for case suffix predictions using this sampling approach, and experimentally show that the enhanced approach outperforms the unenhanced ones on event logs that exhibits a high frequency of repeated activities with respect to both control-flow and temporal accuracy measures.

关键词： Process Mining Predictive Process Monitoring Sequence Prediction Deep Learning

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Verification of Correctness and Data-Flow Properties for Workflow Processes in Maude 25th

Verification of Correctness and Data-Flow Properties for Wor...

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25th International Conference on Enterprise information Systems (ICEIS)

作者： Captarencu, Oana Otilia Alexandru Ioan Cuza Univ Iasi Romania

ISBN: (纸本)9783031647543;9783031647550

A business process is composed of interrelated tasks, executed inside an organization in order to accomplish a specific business goal. A workflow is the automation of a business process that can be executed by an information system. Besides the tasks (which constitute the control-flow level), the process also involves data information (which constitutes the data-flow level). The correctness of the processes is critical for ensuring the business goals and should be achieved both at the control-flow and at the data-flow level. In this paper we use Workflow Nets with Data for modelling the workflow processes with data and we propose the specification of Workflow Nets with Data as rewrite theories in the rewriting logic based language Maude. This approach will permit the use of model checking techniques to verify the correctness of the workflows, detect various data-flow anomalies and verify specific properties at the data-flow level.

关键词： Workflow processes correctness Data-flow errors Petri nets Maude Rewriting logic Model checking

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Turning Logs into Lumber: Preprocessing Tasks in Process Mining 5th

Turning Logs into Lumber: Preprocessing Tasks in Process Min...

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5th International Conference on Process Mining (ICPM)

作者： Liu, Ying Dani, Vinicius Stein Beerepoot, Iris Lu, Xixi Univ Utrecht Utrecht Netherlands

ISBN: (纸本)9783031561061;9783031561078

Event logs are invaluable for conducting process mining projects, offering insights into process improvement and data-driven decision-making. However, data quality issues affect the correctness and trustworthiness of these insights, making preprocessing tasks a necessity. Despite the recognized importance, the execution of preprocessing tasks remains ad-hoc, lacking support. This paper presents a systematic literature review that establishes a comprehensive repository of preprocessing tasks and their usage in case studies. We identify six high-level and 20 low-level preprocessing tasks in case studies. Log filtering, transformation, and abstraction are commonly used, while log enriching, integration, and reduction are less frequent. These results can be considered a first step in contributing to more structured, transparent event log preprocessing, enhancing process mining reliability.

关键词： Log preprocessing Process mining Event log

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