TY  - GEN
AU  - Consoli,Sergio
AU  - Reforgiato Recupero,Diego
AU  - Saisana,Michaela
AU  - Consoli,Sergio
AU  - Reforgiato Recupero,Diego
AU  - Saisana,Michaela
TI  - Data Science for Economics and Finance : Methodologies and Applications
SN  - 978-3-030-66891-4
PY  - 2021///
PB  - Springer Nature
KW  - Data mining
KW  - bicssc
KW  - Machine learning
KW  - Business mathematics & systems
KW  - Public administration
KW  - Information retrieval
KW  - Data Mining and Knowledge Discovery
KW  - Machine Learning
KW  - Business Information Systems
KW  - Big Data/Analytics
KW  - Computer Appl. in Administrative Data Processing
KW  - Information Storage and Retrieval
KW  - IT in Business
KW  - Computer and Information Systems Applications
KW  - Open Access
KW  - Data Mining
KW  - Big Data
KW  - Data Analytics
KW  - Decision Support Systems
KW  - Semantics and Reasoning
KW  - Expert systems / knowledge-based systems
KW  - Information technology: general issues
KW  - Data warehousing
N1  - Open Access
N2  - 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
UR  - https://library.oapen.org/bitstream/20.500.12657/49505/1/9783030668914.pdf
UR  - https://library.oapen.org/bitstream/20.500.12657/49505/1/9783030668914.pdf
UR  - https://directory.doabooks.org/handle/20.500.12854/70804
ER  -