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dc.contributor.editorConsoli, Sergio
dc.contributor.editorReforgiato Recupero, Diego
dc.contributor.editorSaisana, Michaela
dc.description.abstractThis 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.
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
dc.subject.classificationbic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJQ Business mathematics & systems
dc.subject.classificationbic Book Industry Communication::J Society & social sciences::JP Politics & government::JPP Public administration
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UN Databases::UNH Information retrieval
dc.subject.otherData Mining and Knowledge Discovery
dc.subject.otherMachine Learning
dc.subject.otherBusiness Information Systems
dc.subject.otherBig Data/Analytics
dc.subject.otherComputer Appl. in Administrative Data Processing
dc.subject.otherInformation Storage and Retrieval
dc.subject.otherIT in Business
dc.subject.otherComputer and Information Systems Applications
dc.subject.otherOpen Access
dc.subject.otherData Mining
dc.subject.otherBig Data
dc.subject.otherData Analytics
dc.subject.otherDecision Support Systems
dc.subject.otherSemantics and Reasoning
dc.subject.otherExpert systems / knowledge-based systems
dc.subject.otherBusiness mathematics & systems
dc.subject.otherPublic administration
dc.subject.otherInformation technology: general issues
dc.subject.otherInformation retrieval
dc.subject.otherData warehousing
dc.titleData Science for Economics and Finance
dc.title.alternativeMethodologies and Applications
oapen.grant.number[grantnumber unknown]

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open access
Except where otherwise noted, this item's license is described as open access