Second International IEEE Workshop on Experimental Economics and Machine Learning
In conjunction with IEEE ICDM 2013 (December 7, Dallas, Texas, USA)
As a part of renowned international conferences on different branches of machine learning, this workshop intends to integrate scientists from experimental economics with those from AI & Data Mining. First workshop – EEML 2012 – has been successfully accomplished at ICFCA 2012 and we look forward to encourage more and more researchers' interactions from both fields.
In Experimental Economics, laboratory and field experiments are conducted on subjects in order to improve theoretical knowledge about human behavior in interactions. Although paying different amounts of money restricts the preferences of the subjects in experiments, the exclusive application of analytical game theory does not suffice to explain the recorded data. It exacts the development and evaluation of more sophisticated models. The research area additionally includes experiments, where human subjects are involved into an interaction with automated agents. Nowadays experiments are conducted using state-of-art software like z-Tree, which produces huge text data sets.
The more data is used for the evaluation, the more of statistical significance can be achieved. Since huge amounts of behavioral data are required to be scanned for regularities and automated agents are required to simulate and to intervene human interactions, Data Mining is the tool of choice for the research in Experimental Economics. We hope that this workshop associated with the conference and other related workshops will help to gather researchers from data analysis and economic communities in order to gain the beneficial results.
- Economical Applications of Machine Learning
- Economical Innovations and Data Mining
- Experimental Economics and Complex Networks
- Econometrics VS Machine Learning & Data Mining
- Human Behavior Modeling and Game Theory
- Innovative applications of Concept Lattices in Economics & Data Mining
- Interdisciplinary Data Science
- Knowledge Discovery in Economics Domain
- Machine Learning for Social Sciences
- New Modeling Languages for Economics
(Bayes and Markov Nets, Petri Nets etc.)
- Ontologies for Economics
- Real Data Mining Projects
- Rustam Tagiew, Qlaym GmbH, Düsseldorf, Germany
- Dmitry Ignatov, National Research University Higher School of Economics, Moscow, Russia
- Fadi Amroush, Granada Lab of Behavioral Economics (GLOBE), Granada, Spain
- Aleksandr Karpov, National Research University Higher School of Economics, Russia
- Alexander Panchenko, Université catholique de Louvain, Belgium
- Antonio Gabriel López Herrera, Department of Computer Science and Artificial Intelligence, Spain
- Boris Galitsky, e-Bay Inc, USA
- Boris Mirkin, National Research University Higher School of Economics, Russia
- Daniel Karabekyan, National Research University Higher School of Economics, Russia
- Guido Dedene, Katholieke Universiteit Leuven, Belgium
- Heather D. Pfeiffer, Akamai Physics Inc, USA
- Irina Efimenko, National Research University Higher School of Economics, Russia
- Jonas Poelmans, Katholieke Universiteit Leuven, Belgium
- Leonid Zhukov, National Research University Higher School of Economics, Russia
- Malay Bhattacharyya, University of Kalyani, India
- Mikhail Khachay, Institute of Mathematics and Mechanics, Ural Branch of RAS, Ekaterinburg, Russia
- Mykola Pechenizkiy, Eindhoven Technical University, The Netherlands
- Nicola Vitucci, Politecnico di Milano, Italy
- Nikolaos Georgantzis,University of Granada & Universitat Jaume I, Spain
- Olga Barinova, Moscow State University, Russia
- Paul Elzinga, Katholieke Universiteit Leuven, Belgium and Amsterdam-Amstelland police, The Netherlands
- Pouya Dehghani Tafti, Qlaym GmbH
- Rostislav Yavorskiy, Skolkovo Foundation, Russia
- Sergei Kuznetsov, National Research University Higher School of Economics, Russia
- Simon Polovina, Sheffield Hallam University, UK
- T.L. Hoang, Eindhoven Technical University, The Netherlands
- Vladimir Khoroshevsky, Computing Centre of Russian Academy of Sciences, Russia
- Vlado Menkovski, Eindhoven Technical University, The Netherlands
- Xenia Naidenova, Military Medical Academy, St. Petersburg, Russia
- Yevgenya Kovalchuk, University of Essex, UK
DEADLINE POSTPONED August 17, 2013: Due date for full workshop papers
September 24, 2013: Notification of paper acceptance to authors
December 7, 2013: Day of workshop
December 7: IEEE EEML 2013 WORKSHOP PRELIMINARY SCHEDULE
Address: Sheraton hotel 400 N. Olive Street Dallas, Texas 75201
9.00 - 9.10 – Opening words
9.10 - 10.00 – Keynote Talk
Edward M.L. Peters The End of Economics as We Know It: How service bundles and the discovery of values leaks and imperfections will change the economic landscape.
10:00 - 10:30 – Coffee Break
11.00 - 12.00 – EEML Session 1
Emma L. Tonkin and Heather D. Pfeiffer, Zombies Walk Among Us: Cross-platform data mining for event monitoring
Edward M.L. Peters, Guido Dedene, and Jonas Poelmans, Empirical Discovery of Potential Value Leaks in Processes by means of Formal Concept Analysis
12:00 - 14:00 – Lunch
14.00 - 15.00 – EEML Session 2
Alexander Porshnev, Ilya Redkin, and Alexey Shevchenko, Machine learning in prediction of stock market indicators based on historical data and data from Twitter sentiment analysis.
Rustam Tagiew, Dmitry Ignatov, and Fadi Amroush, Social Learning in Networks: Extraction of Deterministic Rules
15:00 - 15:30 – Coffee Break
15.30 - 16.00 – EEML Session 3
Anastasia Bezzubtseva, The Early Booking Effect and Other Determinants of Hotel Room Prices in Europe
16.00-16.15 – Future EEML plans and Closing words
All attendees to the workshop are required to register as participants of IEEE ICDM 2013. Information regarding registration is available by the conference organization on the conference site http://icdm2013.rutgers.edu/registration
ICDM has the unique tradition that all accepted workshop papers are published in formal proceedings by the IEEE Computer Society Press. The proceeding will be released in the IEEE Digital Library as well. This requires ICDM to uphold a very standard of quality for all workshop contributions.
1) Paper submissions is limited to a maximum of *8* pages, and follow the IEEE ICDM format requirements http://icdm2013.rutgers.edu/author-instructions
2) Submissions can be done over
3) Each submitted paper is to be carefully reviewed by at least two, preferably three, knowledgeable and experienced reviewers.
4) Every accepted paper is invited to be presented at the workshop date.
As by the ICDM tradition, at submission of papers for the conference, authors can indicate whether they want their papers fast-tracked to a workshop. These papers will be transferred from the main conference review track to the indicated workshop review track.
Once the decision on paper acceptance has been made, the authors will be notified that camera-ready versions of their papers should be prepared and submitted through the IEEE ICDM Workshop CyberChair submission system. Due to the strict production schedule of IEEE Press, these deadlines cannot be postponed.
EEML 2012 Proceedings can be found by the following link: http://ceur-ws.org/Vol-870/
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