Einzeltreffer — DigiBib

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Titel:	Data Science for Economics and Finance
Autor/in / Beteiligte Person:	Consoli, Sergio ; Reforgiato Recupero, Diego ; Saisana, Michaela
Link:	View Record from OAPEN (Volltext)
Veröffentlichung:	Springer Nature; Springer, 2021
Medientyp:	E-Book
Umfang:	355
ISBN:	978-3-030-66891-4 (print) ; 978-3-662-63021-1 (print) ; 3-030-66891-6 (print) ; 3-662-63021-4 (print)
DOI:	10.1007/978-3-030-66891-4
Schlagwort:	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 bic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJQ Business mathematics & systems bic Book Industry Communication::J Society & social sciences::JP Politics & government::JPP Public administration bic Book Industry Communication::U Computing & information technology::UN Databases::UNH Information retrieval
Sonstiges:	Nachgewiesen in: OAPEN Library Sprachen: English Collection: Books ; Imported or submitted locally Original Material: 3983007a-5726-4f1e-b9df-3fbc771f2916 ; 6c6992af-b843-4f46-859c-f6e9998e40d5 Contents Note: [grantnumber unknown] Document Type: book File Description: application/pdf Language: English Rights: Attribution 4.0 International ; URL: https://creativecommons.org/licenses/by/4.0/ Notes: ONIX_20210614_9783030668914_13 ; https://www.springer.com/9783662630211 ; European Commission

Klicken Sie ein Format an und speichern Sie dann die Daten oder geben Sie eine Empfänger-Adresse ein und lassen Sie sich per Email zusenden.

BibTeX Citavi, JabRef, u.a.
(Literaturverwaltung)

PDF kein Volltext!
(Merkzettel, Notizen)

RIS Endnote, Citavi u.a.
(Literaturverwaltung)

MODS
(XML zur Weiterverarbeitung)

oder

Wählen Sie das für Sie passende Zitationsformat und kopieren Sie es dann in die Zwischenablage, lassen es sich per Mail zusenden oder speichern es als PDF-Datei.

Gewünschter Zitations-Stil:

oder

Bitte prüfen Sie, ob die Zitation formal korrekt ist, bevor Sie sie in einer Arbeit verwenden. Benutzen Sie gegebenenfalls den "Exportieren"-Dialog, wenn Sie ein Literaturverwaltungsprogramm verwenden und die Zitat-Angaben selbst formatieren wollen.

Data Science for Economics and Finance