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MIDAS 2016 : The First Workshop on MIning DAta for financial applicationS @ECML-PKDD 2016

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Link: http://networks.imtlucca.it/submission
 
When Sep 19, 2016 - Sep 19, 2016
Where Riva del Garda (Italy)
Submission Deadline Jul 11, 2016
Notification Due Jul 25, 2016
Final Version Due Aug 8, 2016
Categories    data mining   machine learning   finance
 

Call For Papers

=================================================================================
MIDAS 2016
The First Workshop on MIning DAta for financial applicationS
September 19, 2016 - Riva del Garda, Italy
http://networks.imtlucca.it/conferences/midas

in conjunction with

ECML-PKDD 2016
The European Conference on Machine Learning and Practice of Knowledge Discovery
September 19-23, 2016 - Riva del Garda, Italy
http://www.ecmlpkdd2016.org
=================================================================================

We invite submissions to the MIDAS Workshop on MIning DAta for financial applicationS,
to be held in conjunction with ECML-PKDD 2016 - European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery.

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 12 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 6 pages long, presenting work-in-progress.
- Extended abstracts: up to 2 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=midas2016.
Papers must be written in English and formatted according to the ECML-PKDD 2016
submission guidelines available at http://www.ecmlpkdd2016.org/submission.html.

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 workshop proceedings, which will be published online
as a volume of the CEUR Workshop Proceedings publication service (http://ceur-ws.org/).
The CEUR service ensures that the published papers are permanently available and citable.
CEUR Workshop Proceedings are indexed by major digital libraries
(e.g., DBLP, GoogleScholar, CiteSeerX).

Additionally, based on the success of the workshop, extended versions of selected papers
will be published either as a post-proceeding volume of the Springer LNAI series or as a
special issue of a premier journal in the fields of interest of the workshop.


IMPORTANT DATES
---------------
Submission deadline: July 11, 2016
Acceptance notification: July 25, 2016
Camera-ready deadline: August 8, 2016
Workshop date: September 19, 2016


INVITED SPEAKERS
-----------------------
Prof. Fabrizio Lillo, Scuola Normale Superiore, Pisa, Italy


PROGRAM COMMITTEE
-----------------------------
Aris Anagnostopoulos, Sapienza University of Rome
Annalisa Appice, University of Bari
Xiao Bai, Yahoo!
Nicola Barbieri, Tumblr
Paolo Barucca, Scuola Normale Superiore
Michele Berlingerio, IBM Research
Annalina Caputo, University of Bari
Gianbiagio Curato, Scuola Normale Superiore
Carlotta Domeniconi, George Mason University
Debora Donato, StumbleUpon
Andrea Ferretti, UniCredit
Ruth Garcia Gavilanes, Oxford Internet Institute
Sara Hajian, Eurecat
Roberto Interdonato, University of Calabria
Andreas Kaltenbrunner, Eurecat
Dragi Kocev, Jozef Stefan Institute
Nicolas Kourtellis, Telefonica Research
Iordanis Koutsopoulos, Athens University of Economics and Business
Donato Malerba, University of Bari
Yelena Mejova, Qatar Computing Research Institute
Davide Mottin, Hasso Plattner Institute
Giuseppe Nicosia, University of Catania
Marcello Paris, UniCredit
Stefano Pascolutti, UniCredit
Alvin Pastore, University of Sheffield
Giovanni Ponti, ENEA
Aleksandra Rashkovska, Jo┼żef Stefan Institute
Giovanni Stilo, Sapienza University of Rome
Antti Ukkonen, Finnish Institute of Occupational Health
Edoardo Vacchi, UniCredit
Tim Weninger, University of Notre Dame
Giovanni Zappella, UniCredit


ORGANIZERS
----------------
Ilaria Bordino, UniCredit, R&D Dept., Italy
Guido Caldarelli, IMT Institute for Advanced Studies Lucca, Italy
Fabio Fumarola, UniCredit, R&D Dept., Italy
Francesco Gullo, UniCredit, R&D Dept., Italy
Tiziano Squartini, IMT Institute for Advanced Studies Lucca, Italy

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