Data Science-Analytics and Applications [electronic resource] : Proceedings of the 5th International Data Science Conference-iDSC2023 / edited by Peter Haber, Thomas J. Lampoltshammer, Manfred Mayr.

Colaborador(es): Haber, Peter [editor.] | Lampoltshammer, Thomas J [editor.] | Mayr, Manfred [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: X, 104 p. 41 illus., 36 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031421716Tema(s): Artificial intelligence -- Data processing | Application software | Data Science | Computer and Information Systems ApplicationsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 005.7 Clasificación LoC:Q336Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer Nature eBookResumen: 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.
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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.

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.

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