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Titlebook: Business Information Systems Workshops; BIS 2021 Internation Witold Abramowicz,Sören Auer,Milena Stróżyna Conference proceedings 2022 Sprin

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发表于 2025-3-21 16:32:57 | 显示全部楼层 |阅读模式
期刊全称Business Information Systems Workshops
期刊简称BIS 2021 Internation
影响因子2023Witold Abramowicz,Sören Auer,Milena Stróżyna
视频video
学科分类Lecture Notes in Business Information Processing
图书封面Titlebook: Business Information Systems Workshops; BIS 2021 Internation Witold Abramowicz,Sören Auer,Milena Stróżyna Conference proceedings 2022 Sprin
影响因子This book constitutes revised papers from the eight workshops which were held during June 2021 at the 24th International Conference on Business Information Systems, BIS 2021. The conference was planned to take place in Hannover, Germany, and changed to a fully online event due to the COVID-19 pandemic.  There was a total of 67 submissions to all workshops of which 31papers were accepted for publication. The workshops included in this volume are:   AKTB 2021: 12.th. Workshop on Applications of Knowledge-Based Technologies in Business BisEd 2021: BIS Education: Trends and Challenges DigBD 2021: 1.st. Workshop on Digitization in the Flux of Big Data Scenarios DigEx 2021: 3rd International Workshop on transforming the Digital Customer ExperienceiCRM 2021: 6th International Workshop on Integrated Social CRM QOD 2021: 4th Workshop on Quality of Open Data BITA 2021: 12th Workshop on Business and IT AlignmentBSCT 2021: 4th Workshop on Blockchain and Smart Contract Technologies.
Pindex Conference proceedings 2022
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Time-to-Event Modelling for Survival and Hazard Analysis of Stroke Clinical Caseof survival modelling, hazard analysis, risk evaluation are combined for understanding and exploring these data. In this article the time-to-event modelling addresses in-hospital mortality of stroke patients. The clinical data of stroke cases is explored based on the historical records of neurology
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Automatically Extracting Insurance Contract Knowledge Using NLPt related questions from customers. This requires employees to manually search the relevant parameters in the contracts. In this paper, a solution is proposed and evaluated that automatically extracts insurance parameters from contracts using regular expressions and Natural Language Processing. Whil
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Analyzing Medical Data with Process Mining: A COVID-19 Case Studyand complete analysis on patients’ medical data through many branches of data science. In particular, medical records that include timestamps showing the history of a patient have enabled the representation of medical information as sequences of events, effectively allowing to perform process mining
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Problem Domain Example of Knowledge-Based Enterprise Model Usage for Different UML Behavioral Modelstems (IS) engineering process. Enterprise Meta-Model (EMM) presented more than two decades ago justifies EM structure. EM stores problem domain data gathered by analyst and this EM structure can be used for project models creation in IS design phase. Unified Modeling Language (UML) models are one of
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Reconsidering the Challenges of BIS Education in Light of the COVID Pandemicarket and the resulting demand for a combination of up-to-date technical knowledge, organization-centred mindset, and adaptive skills. However, advances in pedagogical methods, changes in the skills of high-school graduates, and widening online options in the wake of the COVID-19 pandemic brought on
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Comparative Analysis of Highly Ranked BIS Degree Programser graduating. Degree programs as well as labour market needs may be compared based on such competences. Developing or redesigning Business Information Systems (BIS) degree programs may utilize offers of competitor institutions as best practices. This was the case at a Hungarian university where the
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Multi-agent System for Weather Forecasting in Indiavel idea of using Multi Agent System (MAS) for weather forecasting, particularly in the Indian context. The proposed approach incorporates a deep neural network model within MAS with a hybrid ANN algorithm to recognize the static and dynamic weather conditions. The approach uses ensemble prediction
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