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Data Science for Economics and Finance [[electronic resource] ] : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana
Data Science for Economics and Finance [[electronic resource] ] : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana
Autore Consoli Sergio
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Springer Nature, 2021
Descrizione fisica 1 online resource (XIV, 355 p. 56 illus., 44 illus. in color.)
Disciplina 006.312
Soggetto topico Data mining
Machine learning
Management information systems
Big data
Application software
Information storage and retrieval
Data Mining and Knowledge Discovery
Machine Learning
Business Information Systems
Big Data/Analytics
Computer Appl. in Administrative Data Processing
Information Storage and Retrieval
Soggetto non controllato Data Mining and Knowledge Discovery
Machine Learning
Business Information Systems
Big Data/Analytics
Computer Appl. in Administrative Data Processing
Information Storage and Retrieval
IT in Business
Computer and Information Systems Applications
Open Access
Data Mining
Big Data
Data Analytics
Decision Support Systems
Semantics and Reasoning
Expert systems / knowledge-based systems
Business mathematics & systems
Public administration
Information technology: general issues
Information retrieval
Data warehousing
ISBN 3-030-66891-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Data Science Technologies in Economics and Finance: A Gentle Walk-In -- Supervised Learning for the Prediction of Firm Dynamics -- Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting -- Machine Learning for Financial Stability -- Sharpening the Accuracy of Credit Scoring Models with Machine Learning Algorithms -- Classifying Counterparty Sector in EMIR Data -- Massive Data Analytics for Macroeconomic Nowcasting -- New Data Sources for Central Banks -- Sentiment Analysis of Financial News: Mechanics and Statistics -- Semi-supervised Text Mining for Monitoring the News About the ESG Performance of Companies -- Extraction and Representation of Financial Entities from Text -- Quantifying News Narratives to Predict Movements in Market Risk -- Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets? -- Network Analysis for Economics and Finance: An application to Firm Ownership.
Record Nr. UNISA-996464413703316
Consoli Sergio  
Springer Nature, 2021
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Data Science for Economics and Finance : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana
Data Science for Economics and Finance : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana
Autore Consoli Sergio
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Springer Nature, 2021
Descrizione fisica 1 online resource (XIV, 355 p. 56 illus., 44 illus. in color.)
Disciplina 006.312
Soggetto topico Data mining
Machine learning
Management information systems
Big data
Application software
Information storage and retrieval
Data Mining and Knowledge Discovery
Machine Learning
Business Information Systems
Big Data/Analytics
Computer Appl. in Administrative Data Processing
Information Storage and Retrieval
Soggetto non controllato Data Mining and Knowledge Discovery
Machine Learning
Business Information Systems
Big Data/Analytics
Computer Appl. in Administrative Data Processing
Information Storage and Retrieval
IT in Business
Computer and Information Systems Applications
Open Access
Data Mining
Big Data
Data Analytics
Decision Support Systems
Semantics and Reasoning
Expert systems / knowledge-based systems
Business mathematics & systems
Public administration
Information technology: general issues
Information retrieval
Data warehousing
ISBN 3-030-66891-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Data Science Technologies in Economics and Finance: A Gentle Walk-In -- Supervised Learning for the Prediction of Firm Dynamics -- Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting -- Machine Learning for Financial Stability -- Sharpening the Accuracy of Credit Scoring Models with Machine Learning Algorithms -- Classifying Counterparty Sector in EMIR Data -- Massive Data Analytics for Macroeconomic Nowcasting -- New Data Sources for Central Banks -- Sentiment Analysis of Financial News: Mechanics and Statistics -- Semi-supervised Text Mining for Monitoring the News About the ESG Performance of Companies -- Extraction and Representation of Financial Entities from Text -- Quantifying News Narratives to Predict Movements in Market Risk -- Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets? -- Network Analysis for Economics and Finance: An application to Firm Ownership.
Record Nr. UNINA-9910484567403321
Consoli Sergio  
Springer Nature, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Science for Healthcare : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Milan Petković
Data Science for Healthcare : Methodologies and Applications / / edited by Sergio Consoli, Diego Reforgiato Recupero, Milan Petković
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (367 pages)
Disciplina 610.285
Soggetto topico Data mining
Artificial intelligence
Health informatics
Information storage and retrieval
Application software
Data Mining and Knowledge Discovery
Artificial Intelligence
Health Informatics
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
ISBN 3-030-05249-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I: Challenges and Basic Technologies -- Data Science in healthcare: benefits, challenges and opportunities -- Introduction to Classification Algorithms and their Performance Analysis using Medical Examples -- The role of deep learning in improving healthcare -- Part II: Specific Technologies and Applications -- Making effective use of healthcare data using data-to-text technology -- Clinical Natural Language Processing with Deep Learning -- Ontology-based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy on Social Robots -- Assistive Robots for the elderly: innovative tools to gather health relevant data -- Overview of data linkage methods for integrating separate health data sources -- A Flexible Knowledge-based Architecture For Supporting The Adoption of Healthy Lifestyles with Persuasive Dialogs -- Visual Analytics for Classifier Construction and Evaluation for Medical Data -- Data Visualization in Clinical Practice -- Using process analytics to improve healthcare processes -- A Multi-Scale Computational Approach to Understanding Cancer Metabolism -- Leveraging healthcare financial analytics for improving the health of entire populations.
Record Nr. UNINA-9910337577203321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui