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Data Management Technologies and Applications: 9th International Conference, DATA 2020, Virtual Event, July 7–9, 2020, Revised Selected Papers de Slimane Hammoudi

Data Management Technologies and Applications: 9th International Conference, DATA 2020, Virtual Event, July 7–9, 2020, Revised Selected Papers: Communications in Computer and Information Science, cartea 1446

Editat de Slimane Hammoudi, Christoph Quix, Jorge Bernardino
en Limba Engleză Paperback – 23 iul 2021
This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. 

The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity.

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Specificații

ISBN-13: 9783030830137
ISBN-10: 3030830136
Pagini: 319
Ilustrații: XII, 319 p. 98 illus., 72 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.47 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

Removing Operational Friction using Process Mining: Challenges Provided by the Internet of Production (IoP).- Efficient Scheduling of Scientifc Workflow Actions in the Cloud based on Required Capabilities.- iTLM-Q: A Constraint-based Q-learning Approach for Intelligent Traffc Light Management.- Open Data in the Enterprise Context: Assessing Open Corporate Data's Readiness for Use.- A Data Science Approach to Explain a Complex Team Ball Game.- Intelligent Public Procurement Monitoring System Powered by Text Mining and Balanced Indicators.- Catalog Integration of Heterogeneous and Volatile Product Data.- Designing an Efficient Gradient Descent based Heuristic for Clusterwise Linear Regression for Large Datasets.-  A Policy-agnostic Programming Language for the International Data Spaces.- Coreset-based Data Compression for Logistic Regression.- Product Classification using Partially Abbreviated Product Names, Brands and Dimensions.- An Environmental Study of French Neighbourhoods.- Phenomena Explanation from Text: Unsupervised Learning of Interpretable and Statistically Significant Knowledge.