Data Science – Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019

Data Science – Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019

Author
Peter Haber, Thomas Lampoltshammer, Manfred Mayr
Publisher
Springer Fachmedien Wiesbaden;Springer Vieweg
Language
German-English
Edition
1. Aufl. 2019
Year
2019
Page
XIV, 102
ISBN
978-3-658-27494-8,978-3-658-27495-5
File Type
pdf
File Size
7.4 MiB

Product Description
This book offers the proceedings of the Second International Data Science Conference (iDSC2019), organized by Salzburg University of Applied Sciences, Austria. The Conference brought together researchers, scientists, and business experts to discuss new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The papers gathered here include case studies of applied techniques, and theoretical papers that push the field into the future. The full-length scientific-track papers on Data Analytics are broadly grouped by category, including Complexity; NLP and Semantics; Modelling; and Comprehensibility. Included among real-world applications of data science are papers on



Exploring insider trading using hypernetworks
Data-driven approach to detection of autism spectrum disorder
Anonymization and sentiment analysis of Twitter posts



Theoretical papers in the book cover such topics as Optimal Regression Tree Models Through Mixed Integer Programming; Chance Influence in Datasets with Large Number of Features; Adversarial Networks ― A Technology for Image Augmentation; and Optimal Regression Tree Models Through Mixed Integer Programming.
Five shorter student-track papers are also published here, on topics such as


State-of-the-art Deep Learning Methods to effect Neural Machine Translation from Natural Language into SQL
A Smart Recommendation System to Simplify Projecting for a HMI/SCADA Platform
 Use of Adversarial Networks as a Technology for Image Augmentation
Using Supervised Learning to Predict the Reliability of a Welding Process

The work collected in this volume of proceedings will provide researchers and practitioners with a detailed snapshot of current progress in the field of data science. Moreover, it will stimulate new study, research, and the development of new applications.





From the Back Cover
Advances in technology and changes in the business and social environment have led to an increasing flood of data, fueling both the need and the desire to generate value from these assets. The emerging field of Data Science is poised to deliver theoretical and practical solutions to the pressing issues of data-driven applications.
The 2nd International Data Science Conference (iDSC2019 / http://www.idsc.at) organized by Salzburg University of Applied Sciences brings together researchers, scientists, and business experts to discuss new ways of embracing agile approaches within the various domains of data science, e.g. machine learning and AI, data mining, visualization and communication, as well as case studies and best practices from leading research institutions and businesses.The proceedings include all full papers presented in the scientific track and the short papers from the student track.

Editors
Peter Haber is a Professor of Information and Communication Technology, in particular for analog and digital signal processing, and responsible coordinator for system theory and electrical engineering at Salzburg University of Applied Sciences. He is a researcher and project manager, leading and coordinating national and international projects in the field of IT and IT management, while also integrating data science solutions at businesses. Since 2009 he has been a member of the international advisory board for the IATED conferences.
Thomas Lampoltshammer is an Assistant Professor for ICT and Deputy Head of the Centre for E-Governance at the Department of E-Governance and Administration, Danube University Krems, Austria. His current research focus is on the domain of data governance, the effects of ICT application in a connected society, and the effects on a data-driven society. He has a substantial background in the design and implementation of expert and decision-making systems, data analytics, and semantic-based reasoning. 
Manfred Mayr is the Academic Program Dir

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