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https://ceur-ws.org/Vol-870/Preface.pdf
Rustam Tagiew, Dmitry I. Ignatov, Alexey A. Neznanov, Jonas Poelmans (Eds.)
EEML 2012 – Experimental Economics in Machine
Learning
Workshop co-located with the 10th International Conference on Formal Concept
Analysis (ICFCA 2012)
May 2012, Leuven, Belgium
i
Volume Editors
Rustam Tagiew
Institute for Computer Science
Technische Universität Freiberg, Germany
Dmitry I. Ignatov
School of Applied Mathematics and Information Science
National Research University Higher School of Economics, Moscow, Russia
Alexey A. Neznanov
School of Applied Mathematics and Information Science
National Research University Higher School of Economics, Moscow, Russia
Jonas Poelmans
Faculty of Business and Economics
Katholieke Universiteit Leuven, Belgium
Printed in Belgium by the Katholieke Universiteit Leuven with ISBN 978-9-08-
140992-6.
The proceedings are also published online on the CEUR-Workshop web site in
a series with ISSN 1613-0073.
Copyright c 2012 for the individual papers by papers’ authors, for the Volume
by the editors. All rights reserved. No part of this publication may be reproduced,
stored in a retrieval system, or transmitted, in any form or by any means without
the prior permission of the copyright owners.
ii
Preface
In Experimental Economics, laboratory and field experiments are conducted on
subjects in order to improve theoretical knowledge about human behavior in in-
teractions. Although paying different amounts of money restricts the preferences
of the subjects in experiments, the exclusive application of analytical game the-
ory does not suffice to explain the recorded data. It exacts the development and
evaluation of more sophisticated models. In some experiments, human subjects
are involved into an interaction with automated agents and these agents are used
for simulating human interactions. The more data is used for the evaluation, the
more of statistical significance can be achieved. Since huge amounts of behav-
ioral data are required to be scanned for regularities and automated agents are
required to simulate and to intervene human interactions, Machine Learning is
the tool of choice for the research in Experimental Economics. Moreover mod-
ern economics extensively involves network structures, which can be modeled as
graphs or more complicated relational structures.
This volume contains the papers presented at the inaugural International
Workshop on Experimental Economics and Machine Learning (EEML 2012) held
on May 9, 2012 at the Katholieke Universiteit Leuven, Belgium. This year the
committee decided to accept 8 full papers for publication in the proceedings and
two abstracts for presentation at the conference. Each submission was reviewed
by on average 3 program committee members. R. Tagiew proposes a new method
for mining determinism in human strategic behavior. N. Buzun et al. present
a comparison of methods and measures for overlapping community detection.
A. Fishkov et al. discuss a new click model for relevance prediction in Web search.
A. Drutsa et al. applied novel data visualisation techniques to socio-semantic
network data. Gilabert et al. made an experimental study on the relationship
between trust and budgetary slack. O. Barinova et al. proposed using online
random forest for interactive image segmentation. A. Bezzubtseva et al. built a
new typology of collaboration platform users. V. Zaharchuk et al. proposed a
new recommender system for interactive radio network services. D. Ignatov et
al. designed a prototype system for collaborative platform data analysis.
We would like to express our gratitude to all contributing authors and re-
viewers, especially to Malay Bhattacharyya, Hoang Thanh Lam, Olga Barinova
and Alexandra Kaminskaya for their enormous efforts. We also want to thank
our sponsors Amsterdam-Amstelland police, IBM Belgium, Research Founda-
tion Flanders, Vlerick Management School, OpenConnect Systems and Higher
School of Economics.
May, 2012 Rustam Tagiew
Leuven Dmitry I. Ignatov
Alexey A. Neznanov
Jonas Poelmans
Organization
The inaugural International Workshop on Experimental Economics and Machine
Learning (EEML 2012) was held on May 9, 2012 at the Katholieke Universiteit
Leuven, Belgium. The workshop was co-located with the 10th International Con-
ference on Formal Concept Analysis (ICFCA-2012).
Program Chairs
Rustam Tagiew Technische Universität Freiberg, Germany
Dmitry I. Ignatov National Research University Higher School of Eco-
nomics, Russia
Alexey A. Neznanov National Research University Higher School of Eco-
nomics, Russia
Jonas Poelmans Katholieke Universiteit Leuven, Belgium
Program Committee
Olga Barinova Moscow State University, Russia
Elvina Bayburina National Research University Higher School of Eco-
nomics, Russia
Malay Bhattacharyya Indian Statistical Institute, India
Guido Dedene Katholieke Universiteit Leuven, Belgium
Irina Efimenko National Research University Higher School of Eco-
nomics, Russia
Boris Galitsky University of Girona, Spain
Hoang Thanh Lam Eindhoven Technical University, The Netherlands
Daniel Karabekyan National Research University Higher School of Eco-
nomics, Russia
Aleksandr Karpov National Research University Higher School of Eco-
nomics, Russia
Mikhail Khachay Institute of Mathematics and Mechanics of Russian
Academy of Sciences, Russia
Vladimir Khoroshevsky Dorodnicyn Computer Centre of Russian Academy
of Sciences, Russia
Vlado Menkovski Eindhoven Technical University, The Netherlands
Xenia Naidenova Military Medical Academy, Russia
Sergey Nikolenko Steklov Mathematical Institute of Russian Academy
of Sciences, Russia
Mykola Pechenizkiy Eindhoven Technical University, The Netherlands
Artem Revenko Technische Universität Dresden, Germany
Stijn Viaene Katholieke Universiteit Leuven, Belgium
Nicola Vitucci Politecnico di Milano, Italy
Rostislav Yavorsky Witology, Russia
Leonid Zhukov National Research University Higher School of Eco-
nomics, Russia
Sofia Kiselgof National Research University Higher School of Eco-
nomics, Russia
Additional Reviewers
Tapas Bhadra Indian Statistical Institute, India
Saurav Mallik Indian Statistical Institute, India
Dmitry Zhivotvorev Yandex and NRU HSE, Russia
Sponsoring Institutions
Amsterdam-Amstelland police, The Netherlands
IBM, Belgium
OpenConnect Systems, USA
Research Foundation Flanders, Belgium
Vlerick Management School, Belgium
National Research University Higher of School Economics, Russia
v
Table of Contents
Regular Papers
Online Random Forest for Interactive Image Segmentation . . . . . . . . . . . . . 1
Olga Barinova, Roman Shapovalov, Sergey Sudakov and Alexander Velizhev
A New Typology of Collaboration Platform Users . . . . . . . . . . . . . . . . . . . . . 9
Anastasia Bezzubtseva and Dmitry Ignatov
Innovative Methods and Measures in Overlapping Community Detection . 20
Nazar Buzun and Anton Korshunov
Socio-Semantic Network Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Alexey Drutsa and Konstantin Yavorskiy
A New Click Model for Relevance Prediction in Web Search . . . . . . . . . . . . 39
Alexander Fishkov and Sergey Nikolenko
The Relationship Between Trust and Budgetary Slack: an Experimental
Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Marı́a Gilabert, Susana Gago and David Naranjo-Gil
CrowDM: the System for Collaborative Platform Data Analysis . . . . . . . . . 61
Dmitry I. Ignatov, Alexandra Yu. Kaminskaya, Anastasia A. Bezzubt-
seva, Ekaterina L. Chernyak, Konstantin N. Blinkin, Daniil R. Ne-
dumov, Olga N. Chugunova, Andrey V. Konstantinov, Nikita S. Ro-
mashkin, Fedor V. Strok, Daria A. Goncharova, Rostislav E.Yavorsky
A New Recommender System for the Interactive Radio Network FMhost . 72
Dmitry Ignatov, Sergey Nikolenko, Vasily Zaharchuk and Andrey Kon-
stantinov
Mining Determinism in Human Strategic Behavior . . . . . . . . . . . . . . . . . . . . 85
Rustam Tagiew
Abstracts
Criteria Formation of Effective High-School Graduates Employment
Based upon Data Mining Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
Yuliya Akhmayzyanova and Irina Bolodurina
Image Processing Using Dynamical NK-Networks, Consisting of Binary
Logical Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Daria Puchkova
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94