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Mining Data for Financial Applications : 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / edited by Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Ponti.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11985
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 11985
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer vision.
- Computer engineering.
- Computer networks.
- Electronic commerce.
- Social sciences-Data processing.
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Communication Networks.
- e-Commerce and e-Business.
- Computer Application in Social and Behavioral Sciences.
- Local Subjects:
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Communication Networks.
- e-Commerce and e-Business.
- Computer Application in Social and Behavioral Sciences.
- Physical Description:
- 1 online resource (IX, 133 pages) : 37 illustrations, 27 illustrations in color.
- Edition:
- 1st ed. 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held in conjunction with ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.
- Contents:
- MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning
- Curriculum Learning in Deep Neural Networks for Financial Forecasting
- Representation Learning in Graphs for Credit Card Fraud Detection
- Firms Default Prediction with Machine Learning
- Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting
- Mining Business Relationships from Stocks and News
- Mining Financial Risk Events from News and Assessing their impact on Stocks
- Monitoring the Business Cycle with Fine-grained, Aspect-based Sentiment Extraction from News
- Multi-step Prediction of Financial Asset Return Volatility Using Parsimonious Autoregressive Sequential Model
- Big Data Financial Sentiment Analysis in the European Bond Markets
- A Brand Scoring System for Cryptocurrencies Based on Social Media Data.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-37720-5
- 9783030377205
- Access Restriction:
- Restricted for use by site license.
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