Mining Data for Financial Applications: 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers: Lecture Notes in Computer Science, cartea 12591
Editat de Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severinien Limba Engleză Paperback – 15 ian 2021
*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.
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Specificații
ISBN-13: 9783030669805
ISBN-10: 3030669807
Pagini: 151
Ilustrații: X, 151 p. 64 illus., 50 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.24 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3030669807
Pagini: 151
Ilustrații: X, 151 p. 64 illus., 50 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.24 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA).- How much does Stock Prediction improve with Sentiment Analysis?.- Applying Machine Learning to Predict Closing Prices in Stock Market: a case study.- Financial Fraud Detection with Improved Neural Arithmetic Logic Units.- Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets.- Multi-Objective Particle Swarm Optimization for Feature Selection in Credit Scoring.- A comparative analysis of Temporal Long Text Similarity: Application to Financial Documents.- Ranking Cryptocurrencies by Brand Importance: a Social Media Analysis in ENEAGRID.- Towards the Prediction of Electricity Prices at the Intraday Market Using Shallow and Deep-Learning Methods.- Neither in the Programs Nor in the Data: Mining the Hidden Financial Knowledge with Knowledge Graphs and Reasoning.- Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting.
Textul de pe ultima copertă
“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.