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Mining Data for Financial Applications

5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers

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15 January 2021
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This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.*

The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.

*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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    Product Details
    ISBN-13
    9783030669805
    Author
    Valerio Bitetta
    Publisher
    Springer Nature B.V.
    Published
    15 January 2021
    Format
    Paperback / softback

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    $111.59
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Mining Data for Financial Applications

    $111.59

    Description

    This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.*

    The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.

    *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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