Data Science—Analytics and Applications
Springer International Publishing (Verlag)
978-3-031-42170-9 (ISBN)
Based on the overall digitalization in all spheres of our lives, Data Science and Artificial Intelligence (AI) are nowadays cornerstones for innovation, problem solutions, and business transformation. Data, whether structured or unstructured, numerical, textual, or audiovisual, put in context with other data or analyzed and processed by smart algorithms, are the basis for intelligent concepts and practical solutions. These solutions address many application areas such as Industry 4.0, the Internet of Things (IoT), smart cities, smart energy generation, and distribution, and environmental management. Innovation dynamics and business opportunities for effective solutions for the essential societal, environmental, or health challenges, are enabled and driven by modern data science approaches.
However, Data Science and Artificial Intelligence are forming a new field that needs attention and focused research. Effective data science is only achieved in a broad and diverse discourse- when data science experts cooperate tightly with application domain experts and scientists exchange views and methods with engineers and business experts. Thus, the 5th International Data Science Conference (iDSC 2023) brings together researchers, scientists, business experts, and practitioners to discuss new approaches, methods, and tools made possible by data science.
lt;p>Peter Haber is Assistant 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, University for Continuing Education Krems, Austria. His current research focuses 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 designing and implementing expert and decision-making systems, data analytics, and semantic-based reasoning.
Manfred Mayr is the Academic Program Director for "Business Informatics and Digital Transformation" as well as the department head for "Management & Communications" in the Department of "Information Technologies and Digitalisation" and professor for IT-Management & Digital Leadership at Salzburg University of Applied Sciences. He is a lecturer at international conferences and the author of various publications in the field of business informatics and business applications. The digitalization of ERP applications in the industrial environment is a long-standing and important field of his research. In addition, he was as projectmanager responsible for several national and international research projects.
Comparison of Clustering Algorithms for Statistical Features of Vibration Data Sets.- Towards Measuring Vulnerabilities and Exposures in Open-Source Packages.- CSRX: A novel Crossover Operator for a Genetic Algorithm applied to the Traveling Salesperson Problem.- First Insight into Social Media User Sentiment Spreading Potential to Enhance the Conceptual Model for Disinformation Detection.- Hateful Messages: A Conversational Data Set of Hate Speech produced by Adolescents on Discord.- Prediction of Tourism Flow with Sparse Geolocation Data.- Popular and on the Rise - But Not Everywhere: COVID-19-Infographics on Twitter.- Taxonomy-enhanced Document Retrieval.- Robustness of Sentiment Analysis of Multilingual Twitter Postings.- Exploratory analysis of the applicability of formalised knowledge to personal experience narration.- Supply Chain Data Spaces - The next generation of data sharing.- Condition Monitoring and Anomaly Detection: Real-world Challenges and Successes.- Towards Validated Head Tracking On Moving Two-Wheelers.- A Framework for Inline Quality Inspection of mechanical components in an industrial production.- A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications.
| Erscheinungsdatum | 06.01.2024 |
|---|---|
| Zusatzinfo | X, 104 p. 41 illus., 36 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 210 x 279 mm |
| Gewicht | 303 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Schlagworte | Applications • Big Data • Computer Science • conference proceedings • Data Science • Informatics • Research |
| ISBN-10 | 3-031-42170-1 / 3031421701 |
| ISBN-13 | 978-3-031-42170-9 / 9783031421709 |
| Zustand | Neuware |
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