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MIDAS 2019 : 4th Workshop on MIning DAta for financial applicationS


When Sep 16, 2019 - Sep 16, 2019
Where Wurzburg, Germany
Submission Deadline Jun 7, 2019
Notification Due Jul 5, 2019
Final Version Due Jul 19, 2019
Categories    data mining   machine learning   financial applications

Call For Papers

MIDAS 2019
The Fourth Workshop on MIning DAta for financial applicationS
September 16, 2019 - Wurzburg, Germany

in conjunction with

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
September 16-20, 2019 - Wurzburg, Germany

We invite submissions to the 4th 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.

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

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,, 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
Papers must be written in English and formatted according to the ECML-PKDD 2019
submission guidelines available at

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*.

Accepted papers will be part of the ECML-PKDD 2019 workshop post-proceedings, which will be published as a Springer LNCS volume.
The proceedings of the past edition of the workshop are available here:

Submission deadline: June 7, 2019
Acceptance notification: July 5, 2019
Camera-ready deadline: July 19, 2019
Workshop date: September 16, 2019


Aris Anagnostopoulos, Sapienza University
Argimiro Arratia, Universitat Politecnica de Catalunya
Antonia Azzini, C2T
Xiao Bai, Yahoo Research
Luca Barbaglia, JRC - European Commission
Ludovico Boratto, Eurecat
Cristian Bravo, University of Southampton
Doug Burdick, IBM Research
Alejandra Cabana, Universitat Autonoma de Barcelona
Olivier Caelen, Atos Wordline
Annalina Caputo, Trinity College Dublin
Sergio Consoli, JRC - European Commission
Carlotta Domeniconi, George Mason University
Wouter Duivesteijn, Eindhoven University of Technology
Roberto Interdonato, CIRAD
Alexandros Iosifidis, Aarhus University
Andreas Kaltenbrunner, NTENT
Dragi Kocev, Jozef Stefan Institute
Nicolas Kourtellis, Telefonica Research
Iordanis Koutsopoulos, Athens University of Economics and Business 
Ralf Krestel, Hasso Plattner Institute
Rajasekar Krishnamurthy, University of Massachusetts Amherst
Elisa Letizia, European Central Bank
Matteo Manca, Zurich Insurance
Stefania Marrara, C2T
Yelena Mejova, ISI Foundation
Davide Mottin, Aarhus University
Luca Rossini, Vrije Universiteit Amsterdam
Carlos Sarraute, Grandata Labs
Tatevik Sekhposyan, Texas A&M University
Letizia Tanca, Politecnico of Milan
Turki Turki, New Jersey Institute of Technology
Ali Caner Turkmen, Bogazici University
Antti Ukkonen, University of Helsinki
Edoardo Vacchi, Red Hat
George Valkanas, Detectica

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
Stefano Pascolutti, UniCredit, R&D Dept., Italy
Giovanni Ponti, ENEA, Portici Research Center, Italy

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