Titlebook: Intelligent Information Systems; CAiSE Forum 2021, Me Selmin Nurcan,Axel Korthaus Conference proceedings 2021 Springer Nature Switzerland A

战神

书目名称Intelligent Information Systems影响因子(影响力)




书目名称Intelligent Information Systems影响因子(影响力)学科排名




书目名称Intelligent Information Systems网络公开度




书目名称Intelligent Information Systems网络公开度学科排名




书目名称Intelligent Information Systems被引频次




书目名称Intelligent Information Systems被引频次学科排名




书目名称Intelligent Information Systems年度引用




书目名称Intelligent Information Systems年度引用学科排名




书目名称Intelligent Information Systems读者反馈




书目名称Intelligent Information Systems读者反馈学科排名

牛的细微差别

Benzodiazepines

先行

Sensor Data Stream Selection and Aggregation for the Ex Post Discovery of Impact Factors on Process ed by process execution data, including (external) sensor data streams, e.g., indicating an overheating machine. Challenges are to select the “right” sensors –possibly a multitude of sensors is available– and to specify how the sensor data streams are aggregated and used to calculate the impact on t

狂热文化

不知疲倦

ISGE: A Conceptual Model-Based Method to Correctly Manage Genome Datathe diagnosis, treatment, and prevention of disease, providing long-term benefits and a transformative impact on personal health. It also has wealth and productivity implications. However, genomics is one of the most complex and data-intensive domains. Fuzzy definitions, data diversity, data heterog

发电机

calamity

Evaluating Fidelity of Explainable Methods for Predictive Process Analyticsiques have been used to increase the accuracy of predictions, the resulting predictive models lack transparency. Explainable machine learning methods can be used to interpret black-box models. However, it is unclear how fit for purpose these methods are in explaining process predictive models. In th

lethargy

Data-Driven Process Performance Measurement and Prediction: A Process-Tree-Based Approach by distilling historical process knowledge based on recorded historical event data. Few techniques focus on the prediction of process performance after process redesign. This paper proposes a foundational framework for a data-driven business process redesign approach, allowing the user to investiga

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