Titlebook: Data Management Technologies and Applications; 9th International Co Slimane Hammoudi,Christoph Quix,Jorge Bernardino Conference proceedings

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iTLM-Q: A Constraint-Based Q-Learning Approach for Intelligent Traffic Light Management,ies. For instance, crowdsourced information from vehicles can be used as input for self-learning systems. In this paper, we propose . based on our previous work . to optimize traffic light management in a privacy-friendly manner. We aim to reduce the overall waiting time and contribute to a smoother

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,Open Data in the Enterprise Context: Assessing Open Corporate Data’s Readiness for Use,ir data increasingly available, open data consumers are reluctant or experience difficulties with using open data. Prior studies have therefore set the focus on open data portals and open data quality, but only few have examined enterprises as consumers of open data. To close this gap, we aim at ass

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Intelligent Public Procurement Monitoring System Powered by Text Mining and Balanced Indicators,te intelligent indicators could potentially be applied throughout the public procurement process. Research is showing that these technologies are not yet firmly established in the public procurement process. However, as presented in this paper, they have the potential to transform this process in va

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Designing an Efficient Gradient Descent Based Heuristic for Clusterwise Linear Regression for Largeegression problems, the data points with similar regression estimates are grouped into the same cluster either due to a business need or to increase the statistical significance of the resulting regression estimates. In this paper, we consider an extension of this problem where data points belonging

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A Policy-Agnostic Programming Language for the International Data Spaces,luable asset, this is a challenge that many companies have to face. This is particularly true as data sharing with third parties is a mandatory component of many modern business models. For its participants, the International Data Spaces (IDS) provide an ecosystem that supports the establishment and

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Product Classification Using Partially Abbreviated Product Names, Brands and Dimensions,and cost-intensive manual process. The basis which many attributes and business processes in master data management depend on is the classification of articles to a certain product category. In this paper we propose a machine learning approach to classify articles according to the Global Product Cla

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