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MIDAS 2021 : 6th Workshop on MIning DAta for financial applicationS | |||||||||||||||
Link: http://midas.portici.enea.it/ | |||||||||||||||
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Call For Papers | |||||||||||||||
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MIDAS 2021 - The Sixth Workshop on MIning DAta for financial applicationS September 13 or 17, 2021 - VIRTUAL http://midas.portici.enea.it in conjunction with ECML-PKDD 2021 - The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases September 13-17, 2021 - VIRTUAL https://2021.ecmlpkdd.org/ ========================================================================================== COVID-19 PLAN ------------- Originally planned to take place in Bilbao, Spain, the COVID-19 pandemic made the ECML-PKDD 2021 conference and all its satellite events -- including MIDAS 2021 -- switch to an ONLINE format. OVERVIEW -------- We invite submissions to the 6th MIDAS Workshop on MIning DAta for financial applicationS, to be held in conjunction with ECML-PKDD 2021 - 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 - Data-driven anti money laundering - Discovering patterns and correlations in financial data - Text mining and NLP for financial applications - Financial network analysis - Time series analysis - Pitfalls identification - Financial knowledge graphs - Reinforcement learning in the financial domain - Explainable AI in financial services 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. All page limits are intended *excluding references*, whuch may take as many additional pages as preferred. Contributions should be submitted in PDF format, electronically, using the workshop submission site at https://easychair.org/conferences/?conf=midas2021. Papers must be written in English and formatted according to the ECML-PKDD 2021 submission guidelines available at https://2021.ecmlpkdd.org/?page_id=1599. 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 2021 workshop post-proceedings, which will be published as a Springer LNCS volume. The proceedings of the past three editions of the workshop are available here: - 2020: https://www.springer.com/978-3-030-66980-5 - 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 (tentative) --------------- Submission deadline: June 25, 2021 Acceptance notification (tentative): July 19, 2021 Early registration: second half of July, 2021 Camera-ready deadline (tentative): July 26, 2020 Workshop date: September 13 or 17, 2021 INVITED SPEAKERS ---------------- TBA PROGRAM COMMITTEE ----------------- Aris Anagnostopoulos, Sapienza University Annalisa Appice, University of Bari Argimiro Arratia, Universitat Politècnica de Catalunya Davide Azzalini, Politecnico of Milan Fabio Azzalini, Politecnico of Milan Antonia Azzini, C2T Xiao Bai, Yahoo Research Andre Baier, Fraunhofer IEE Luca Barbaglia, JRC - European Commission Luigi Bellomarini, Banca d'Italia Ludovico Boratto, Eurecat Cristian Bravo, Western University Douglas Burdick, IBM Research Matteo Catena, SpazioDati Jeremy Charlier, National Bank of Canada Sergio Consoli, JRC - European Commission Carlotta Domeniconi, George Mason University Wouter Duivesteijn, Eindhoven University of Technology Edoardo Galimberti, Inpendent Researcher Cuneyt Gurcan Akcora, University of Manitoba Roberto Interdonato, CIRAD Anna Krause, University of Wurzburg Rajasekar Krishnamurthy, IBM Almaden Malte Lehna, Fraunhofer IEE Domenico Mandaglio, University of Calabria Yelena Mejova, ISI Foundation Sandra Mitrovic, KU Leuven Davide Mottin, Aarhus University Giulia Preti, ISI Foundation Daniel Schloer, University of Wurzburg Christoph Scholz, Fraunhofer IEE Edoardo Vacchi, Red Hat Yongluan Zhou, University of Copenaghen ORGANIZERS ---------- Valerio Bitetta, UniCredit, Italy Ilaria Bordino, UniCredit, Italy Andrea Ferretti, UniCredit, Italy Francesco Gullo, UniCredit, Italy Giovanni Ponti, ENEA, Italy Lorenzo Severini, UniCredit, Italy (midas2021@easychair.org) |
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