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020 _a9783030377205
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024 7 _a10.1007/978-3-030-37720-5
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
_223
245 1 0 _aMining Data for Financial Applications
_h[electronic resource] :
_b4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers /
_cedited by Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Ponti.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aIX, 133 p. 37 illus., 27 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v11985
505 0 _aMQLV: 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.
520 _aThis 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.
650 0 _aArtificial intelligence.
650 0 _aComputer vision.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aElectronic commerce.
650 0 _aSocial sciences
_xData processing.
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputer Vision.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Communication Networks.
650 2 4 _ae-Commerce and e-Business.
650 2 4 _aComputer Application in Social and Behavioral Sciences.
700 1 _aBitetta, Valerio.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aBordino, Ilaria.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFerretti, Andrea.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGullo, Francesco.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPascolutti, Stefano.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPonti, Giovanni.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030377199
776 0 8 _iPrinted edition:
_z9783030377212
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v11985
856 4 0 _uhttps://doi.org/10.1007/978-3-030-37720-5
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
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