Mining Data for Financial Applications: 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers: Lecture Notes in Computer Science, cartea 11985
Editat de Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Pontien Limba Engleză Paperback – 4 ian 2020
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.
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Specificații
ISBN-13: 9783030377199
ISBN-10: 3030377199
Pagini: 133
Ilustrații: IX, 133 p. 37 illus., 27 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.21 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3030377199
Pagini: 133
Ilustrații: IX, 133 p. 37 illus., 27 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.21 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
Cuprins
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.