This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.*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.
| ISBN: | 9783030669805 |
| Publication date: | 15th January 2021 |
| Author: | Valerio Bitetta |
| Publisher: | Springer Nature Switzerland AG |
| Format: | Paperback |
| Pagination: | 151 pages |
| Series: | Lecture Notes in Artificial Intelligence |
| Genres: |
Expert systems / knowledge-based systems Data mining Image processing Computer networking and communications Finance and the finance industry |
This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.*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.
Mining Data for Financial Applications features in the following genres: Expert systems / knowledge-based systems, Data mining, Image processing, Computer networking and communications, Finance and the finance industry
Mining Data for Financial Applications is available in Paperback
Mining Data for Financial Applications was written by Valerio Bitetta and published by Springer Nature Switzerland AG
Mining Data for Financial Applications has 151 pages
Yes it is part of Lecture Notes in Artificial Intelligence series
£44.99