Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12591)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Included in the following conference series:
Conference proceedings info: MIDAS 2020.
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Table of contents (11 papers)
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Mining Data for Financial Applications
Keywords
About this book
The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.
*The workshop was held virtually due to the COVID-19 pandemic.
“Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets” and “Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Editors and Affiliations
Bibliographic Information
Book Title: Mining Data for Financial Applications
Book Subtitle: 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
Editors: Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-66981-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-66980-5Published: 15 January 2021
eBook ISBN: 978-3-030-66981-2Published: 14 January 2021
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: X, 151
Number of Illustrations: 14 b/w illustrations, 50 illustrations in colour
Topics: Artificial Intelligence, Computers and Education, Computer Appl. in Social and Behavioral Sciences, Information Systems Applications (incl. Internet), Data Mining and Knowledge Discovery, Computer Systems Organization and Communication Networks