Name: Data Management Technologies and Applications
Price: 321.23 RON
Availability: OnlineOnly
Author: Slimane Hammoudi
ISBN: 9783030545949

Data Management Technologies and Applications: Communications in Computer and Information Science, cartea 1446

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: 332
Ilustrații: XII, 319 p. 98 illus., 72 illus. in color.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.51 kg
Ediția:1st edition 2021
Editura: Springer
Colecția Communications in Computer and Information Science
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.