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Mining Data for Financial Applications = 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Mining Data for Financial Applications/ edited by Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini.
Reminder of title:	5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers /
other author:	Bitetta, Valerio.
Description:	X, 151 p. 64 illus., 50 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-66981-2
ISBN:	9783030669812

Mining Data for Financial Applications = 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers /
Mining Data for Financial Applications5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers /[electronic resource] :edited by Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini. - 1st ed. 2021. - X, 151 p. 64 illus., 50 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;12591. - Lecture Notes in Artificial Intelligence ;9285.

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.

“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: 9783030669812

Standard No.: 10.1007/978-3-030-66981-2doiSubjects--Topical Terms:

559380
Artificial intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Mining Data for Financial Applications = 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers /
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