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MIDAS 2020 : MIDAS @ECML-PKDD 2020 - 5th Workshop on MIning DAta for financial applicationS

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Link: http://midas.portici.enea.it/
 
When Sep 14, 2020 - Sep 18, 2020
Where Ghent
Submission Deadline Jun 9, 2020
Notification Due Jul 10, 2020
Final Version Due Jul 24, 2020
Categories    data mining   machine learning   finance
 

Call For Papers

===========================================================================================================
MIDAS 2020
The Fifth Workshop on MIning DAta for financial applicationS
September 14 or 18, 2020 - Ghent, Belgium
http://midas.portici.enea.it

in conjunction with

ECML-PKDD 2020
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
September 14-18, 2020 - Ghent, Belgium
https://ecmlpkdd2020.net
===========================================================================================================

We invite submissions to the 5th MIDAS Workshop on MIning DAta for financial applicationS,
to be held in conjunction with ECML-PKDD 2019 - European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases.

Like the famous King Midas, popularly remembered in Greek mythology for his ability to turn
everything he touched with his hand into gold, we believe that the wealth of data generated
by modern technologies, with widespread presence of computers, users and media connected by
Internet, is a goldmine for tackling a variety of problems in the financial domain.

Nowadays, people's interactions with technological systems provide us with gargantuan amounts
of data documenting collective behaviour in a previously unimaginable fashion.
Recent research has shown that by properly modeling and analyzing these massive datasets, or
instance representing them as network structures it is possible to gain useful insights into
the evolution of the systems considered (i.e., trading, disease spreading, political elections).

Investigating the impact of data arising from today's application domains on financial decisions
may be of paramount importance. Knowledge extracted from data can help gather critical information
for trading decisions, reveal early signs of impactful events (such as stock market moves), or
anticipate catastrophic events (e.g., financial crises) that result from a combination of actions,
and affect humans worldwide.

The importance of data-mining tasks in the financial domain has been long recognized.
Core application scenarios include correlating Web-search data with financial decisions,
forecasting stock market, predicting bank bankruptcies, understanding and managing financial risk,
trading futures, credit rating, loan management, bank customer profiling.

The MIDAS workshop is aimed at discussing challenges, potentialities, and applications of
leveraging data-mining tasks to tackle problems in the financial domain.
The workshop provides a premier forum for sharing findings, knowledge, insights, experience
and lessons learned from mining data generated in various application domains.
The intrinsic interdisciplinary nature of the workshop constitutes an invaluable opportunity
to promote interaction between computer scientists, physicists, mathematicians, economists and
financial analysts, thus paving the way for an exciting and stimulating environment involving
researchers and practitioners from different areas.


TOPICS OF INTEREST
------------------
We encourage submission of papers on the area of data mining for financial applications.
Topics of interest include, but are not limited to:

- Forecasting the stock market
- Trading models
- Discovering market trends
- Predictive analytics for financial services
- Network analytics in finance
- Planning investment strategies
- Portfolio management
- Understanding and managing financial risk
- Customer/investor profiling
- Identifying expert investors
- Financial modeling
- Measures of success in forecasting
- Anomaly detection in financial data
- Fraud detection
- Discovering patterns and correlations in financial data
- Text mining and NLP for financial applications
- Financial network analysis
- Time series analysis
- Pitfalls identification


SUBMISSION GUIDELINES
---------------------
We invite submissions of either regular papers (long or short), and extended abstracts:
- Long regular papers: up to 15 pages long (in the Springer LNCS style,
https://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0), reporting on novel,
unpublished work that might not be mature enough for a conference or journal submission.
- Short regular papers: up to 8 pages long, presenting work-in-progress.
- Extended abstracts: up to 4 pages long, referring to recently published work on
the workshop topics, position papers, late-breaking results, or emerging research problems.

Contributions should be submitted in PDF format, electronically, using the workshop
submission site at https://easychair.org/conferences/?conf=midas20201.
Papers must be written in English and formatted according to the ECML-PKDD 2020
submission guidelines available at https://ecmlpkdd2020.net/submissions/researchAndADSTrack/.

Submitted papers will be peer-reviewed and selected on the basis of these reviews.
*If accepted, at least one of the authors must attend the workshop to present the work*.


PROCEEDINGS
-----------
Accepted papers will be part of the ECML-PKDD 2020 workshop post-proceedings, which will be published as a Springer LNCS volume.
The proceedings of the past two editions of the workshop are available here:
- 2019: https://link.springer.com/book/10.1007/978-3-030-37720-5
- 2018: https://link.springer.com/book/10.1007%2F978-3-030-13463-1


IMPORTANT DATES
---------------
Submission deadline: June 9, 2020
Acceptance notification: July 10, 2020
Camera-ready deadline: July 24, 2020
Workshop date: September 14 or 18, 2020


INVITED SPEAKERS
----------------
TBA


PROGRAM COMMITTEE
-----------------
TBA


ORGANIZERS
----------
Valerio Bitetta, UniCredit, R&D Dept., Italy
Ilaria Bordino, UniCredit, R&D Dept., Italy
Andrea Ferretti, UniCredit, R&D Dept., Italy
Francesco Gullo, UniCredit, R&D Dept., Italy
Giovanni Ponti, ENEA, Portici Research Center, Italy
Lorenzo Severini, UniCredit, R&D Dept., Italy
(midas2020-1@easychair.org)

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