CFP: Workshop on Preference Learning at ECML/PKDD-08
Eyke Hüllermeier
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C A L L F O R P A P E R S
W O R K S H O P O N
P R E F E R E N C E L E A R N I N G
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http://www.mathematik.uni-marburg.de/~kebi/ws-ecml-08/
taking place on September 19, 2008, as part of
ECML/PKDD-08, European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases
September 15-19, 2008, Antwerp (Belgium)
Methods for learning preference models and predicting preferences are
among the very recent research trends in fields like machine learning
and knowledge discovery. Approaches relevant to this area range from
learning special types of preference models, such as lexicographic
orders, over collaborative filtering techniques for recommender systems
and ranking techniques for information retrieval, to generalizations of
classification problems such as label ranking. Like other types of
complex learning tasks that have recently entered the stage, preference
learning deviates strongly from the standard problems of classification
and regression. It is particularly challenging as it involves the
prediction of complex structures, such as weak or partial order
relations, rather than single values. Moreover, training input will not,
as it is usually the case, be offered in the form of complete examples
but may comprise more general types of information, such as relative
preferences or different kinds of indirect feedback and implicit
preference information.
This workshop aims at providing a forum for the discussion of recent
advances in the use of machine learning and data mining methods for
problems related to the learning and discovery of preferences, and to
offer an opportunity for researchers and practitioners to identify new
promising research directions. Topics of interest include, but are not
limited to
# quantitative and qualitative approaches to modeling preferences as
well as different forms of feedback and training data;
# learning utility functions and related regression problems;
# preference mining and preference elicitation;
# learning relational preference models;
# embedding of other types of learning problems in the preference
learning framework (such as label ranking, ordinal classification, or
hierarchical classification);
# comparison of different preference learning paradigms (e.g., "big
bang" approaches that use a single model vs. modular approaches that
decompose the learning of preference models into subproblems);
# ranking problems, such as learning to rank objects or to aggregate
rankings;
# scalability and efficiency of preference learning algorithms;
# methods for special application fields, such as web search,
information retrieval, electronic commerce, games, personalization, or
recommender systems;
# connections to other research fields, such as decision theory,
operations research, and social choice theory.
In addition to papers reporting on mature research results we also
encourage submissions presenting more preliminary results and discussing
open problems. Correspondingly, two types of contributions will be
solicited, namely short communications (short talks) and full papers
(long talks).
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SUBMISSION INSTRUCTIONS
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Papers MUST be submitted in Springer LNCS format. There is no strict
page limitation, though 10-15 pages for full papers and 6-8 pages for
short communications should be taken as rough guidelines. Authors'
instructions along with LaTeX and Word macro files are available on the
web at: http://www.springer.de/comp/lncs/authors.html
Submit papers in PDF or PS format. Additional instructions will be given
in due time. Papers should be submitted in pdf format to the following
email address: ey...@mathematik.uni-marburg.de
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IMPORTANT DATES
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JUN 23 Deadline for workshop paper submission
JUL 31 Notification of acceptance for workshop papers
AUG 18 Final camera ready copies due
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WORKSHOP CHAIRS
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Eyke Huellermeier
Department of Mathematics and Computer Science
University of Marburg, Germany
ey...@mathematik.uni-marburg.de
Johannes Fuernkranz
Department of Computer Science
Technical University of Darmstadt, Germany
ju...@ke.informatik.tu-darmstadt.de
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WORKSHOP-WEBSITE
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For further information, please visit the workshop website at
http://www.mathematik.uni-marburg.de/~kebi/ws-ecml-08/
or contact one of the workshop co-chairs.
Eyke Huellermeier and Johannes Fuernkranz
Workshop Chairs