=Paper= {{Paper |id=Vol-1521/preface |storemode=property |title=None |pdfUrl=https://ceur-ws.org/Vol-1521/preface.pdf |volume=Vol-1521 }} ==None== https://ceur-ws.org/Vol-1521/preface.pdf 
                     6th International Workshop on
   Mining Ubiquitous and Social Environments
                  (MUSE)
Introduction
   The 6th International Workshop on Mining Ubiquitous and Social
Environments (MUSE 2015) was held in Porto, Portugal, on September 7th 2015
in conjunction with the European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases (ECML PKDD
2015).

Objectives
    The emergence of ubiquitous computing has started to create new
environments consisting of small, heterogeneous, and distributed devices that
foster the social interaction of users in several dimensions. Similarly, the
upcoming social web also integrates the user interactions in social networking
environments.
    In typical ubiquitous settings, the mining system can be implemented inside
the small devices and sometimes on central servers, for real­time applications,
similar to common mining approaches. However, the characteristics of ubiquitous
and social mining in general are quite different from the current mainstream data
mining and machine learning. Unlike in traditional data mining scenarios, data
does not emerge from a small number of (heterogeneous) data sources, but
potentially from hundreds to millions of different sources. Often there is only
minimal coordination and thus these sources can overlap or diverge in many
possible ways. Steps into this new and exciting application area are the analysis
of this new data, the adaptation of well known data mining and machine learning
algorithms and finally the development of new algorithms.
    Mining big data in ubiquitous and social environments is an emerging area of
research focusing on advanced systems for data mining in such distributed and
network­organized systems. Therefore, for this workshop, we aim to attract
researchers from all over the world working in the field of data mining and
machine learning with a special focus on analyzing big data in ubiquitous and
social environments.
    The goal of this workshop is to promote an interdisciplinary forum for
researchers working in the fields of ubiquitous computing, mobile sensing, social
web, Web 2.0, and social networks which are interested in utilizing data mining
in a ubiquitous setting. The workshop seeks for contributions adopting
state­of­the­art mining algorithms on ubiquitous social data. Papers combining
aspects of the two fields are especially welcome. In short, we want to accelerate
the process of identifying the power of advanced data mining operating on data
collected in ubiquitous and social environments, as well as the process of
advancing data mining through lessons learned in analyzing these new data.
Submissions and Keynotes
   This proceedings volume comprises the contributions to the MUSE 2015
workshop. In total, we accepted four submissions, three full papers and one short
paper, based on the peer­reviews of our program committee. In addition, the
scientific program also featured three invited talks: Michele Berlingerio (IBM
Research and Development, Dublin, Ireland) provided an overview on
Multidimensional Network Analysis including their history, modeling and
analysis aspects and current applications in the context of ubiquitous and social
environments. Markus Schedl (University of Linz, Austria) presented recent
research result about Listener­aware Music Search and Recommendation, also
giving insights in recent prototype applications. Finally, Albert Bifet (Université
Paris­Saclay) showcased recent developments in Data Stream Mining with a
special focus on the Apache SAMOA platform.



Submissions and Keynotes
 ●   Christian Bauckhage, Fraunhofer IAIS, Germany
 ●   Martin Becker, University of Wuerzburg, Germany
 ●   Albert Bifet, University of Waikato, New Zealand
 ●   Stephan Doerfel, University of Kassel, Germany
 ●   Jill Freyne, CSIRO, Australia
 ●   Andreas Hotho, University of Wuerzburg, Germany
 ●   Mark Kibanov, University of Kassel, Germany
 ●   Claudia Mueller­Birn, FU Berlin, Germany
 ●   Nico Piatkowski, TU Dortmund University, Germany
 ●   Haggai Roitman, IBM Research Haifa, Israel
 ●   Philipp Singer, GESIS Koeln, Germany
 ●   Maarten van Someren, University of Amsterdam, The Netherlands
 ●   Gerd Stumme, University of Kassel, Germany
 ●   Arkaitz Zubiaga, University of Warwick, UK



Acknowledgements
   We would like to thank the invited speaker, all the authors who submitted
papers and all the workshop participants. We are also grateful to the members of
the program committee for their thorough and timely work in reviewing
submitted contributions with expertise and patience. Finally, a special thank is
due to both the ECML PKDD Workshop Chairs and the members of the ECML
PKDD Organizing Committee who made this event possible.

Porto, September 2015
Martin Atzmueller
Florian Lemmerich