MUSE 2015 - 6th International Workshop on Mining Ubiquitious and Social Environments (MUSE 2015)
Topics/Call fo Papers
6th International ECML/PKDD 2015 Workshop
on
*MINING UBIQUITOUS AND SOCIAL ENVIRONMENTS*
(MUSE 2015)
http://www.kde.cs.uni-kassel.de/ws/muse2015
***
*** Paper submission deadline: June 22nd, 2015 ***
***
---
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 real-time 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 necessarily emerge
from a small number of data sources, but potentially from hundreds
to millions of different sources. Analysis and prediction using
such data sources provides new challenges for the data mining
and machine learning community.
In a related way, the mining of social data is concerned with
investigating emerging phenomena originating from groups of
individuals and one or more (heterogenous) data sources.
Mining behavioral patterns (e.g., relating to mobility, social
interactions, etc.) in ubiquitous and social environments is an
important up-and-coming area of research focusing on advanced
descriptive and predictive analysis in such distributed and
network-organized contexts.
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 finding behavioral patterns in
ubiquitous and social environments.
GOALS AND AUDIENCE
===
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 state-of-the-art 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.
TOPICS OF INTEREST
===
The topics of the workshop are split roughly into four areas which
include, but are not limited to the following topics:
Ubiquitous Mining:
* Analysis of data from sensors and mobile devices
* Resource-aware algorithms for distributed mining
* Scalable and distributed classification, prediction, and clustering
algorithms
* Mining activity patterns
* Activity recognition
* Mining continuous streams and ubiquitous data
* Online methods for mining temporal, spatial and spatio-temporal data
* Combining data from different sources
Mining Social Data:
* Analysis of social networks and social media
* Mining techniques for social networks and social media
* Algorithms for inferring semantics and meaning from social data
* How social data can be used to mine and create collective intelligence
* Individual and group behavior in social media and social networks
* Analysis of bias in social systems
* Social networks for the collaboration of large communities
* Modeling social behavior
* Novel techniques for mining big data from social media
* Dynamics and evolution patterns of social networks
Ubiquitous and Social Mining
* Personalization and recommendation
* User models and predicting user behavior
* User profiling in ubiquitous and social environments
* Network analysis of social systems
* Discovering social structures and communities
* Mobility mining
* Link prediction
* Analysis of data from crowd-sourcing approaches
Applications:
* Discovering misuse and fraud
* Usage and presentation interfaces for mining and data collection
* Analysis of social and ubiquitous games
* Privacy challenges in ubiquitous and social applications
* Recommenders in ubiquitous and social environments
* Applications of any of the above methods and technologies
We also encourage submissions which relate research results from
other areas to the workshop topics.
SPRINGER BOOK
===
As in the previous years, it is planned to publish revised selected papers
as a volume in the Springer LNCS/LNAI series
WORKSHOP ORGANIZERS
===
* Martin Atzmueller, Knowledge and Data Engineering Group,
University of Kassel, Germany (atzmueller-AT-cs.uni-kassel.de)
* Florian Lemmerich, GESIS - Leibniz Institute for the Social Sciences,
Koeln, Germany (florian.lemmerich-AT-gesis.org)
PROGRAM COMMITTEE
===
Christian Bauckhage, Fraunhofer IAIS, Germany
Martin Becker, University of Wuerzburg, Germany
Albert Bifet, University of Waikato, Germany
Stephan Doerfel, University of Kassel, Germany
Jill Freyne, CSIRO, Australia
Andreas Hotho, University of Wuerzburg, Germany
Mark Kibanov, University of Kassel, Germany
Claudia Mueller-Birn, 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, City University of New York, USA
SUBMISSIONS AND STYLE
===
We invite two types of submissions for this workshop:
* Technical papers in any of the topics of interest of the workshop
(but not limited to them)
* Short position papers in any of the topics of interest of the workshop
(but not limited to them)
Submitted papers will be peer-reviewed and selected on the basis of
these reviews. Accepted papers will be presented at the workshop.
Format requirements for submissions of papers are: Maximum 16
pages, including title page and bibliography for technical
papers. Maximum 8 pages, including title page and bibliography
for short position papers.
All submissions must be entered into the reviewing system:
https://www.easychair.org/conferences/?conf=muse20...
If you have any question please contact the MUSE Organizers. We
recommend to follow the format guidelines of ECML/PKDD (Springer
LNCS), as this will be the required format for accepted papers.
More details can be found on the workshop website:
http://www.kde.cs.uni-kassel.de/ws/muse2015
Important Dates
===
* Paper Submission Deadline: June 22nd, 2015
* Author Notification: July 13th, 2015
* Camera Ready Papers: July 27th, 2016
* Workshop: September 7th, 2015
on
*MINING UBIQUITOUS AND SOCIAL ENVIRONMENTS*
(MUSE 2015)
http://www.kde.cs.uni-kassel.de/ws/muse2015
***
*** Paper submission deadline: June 22nd, 2015 ***
***
---
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 real-time 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 necessarily emerge
from a small number of data sources, but potentially from hundreds
to millions of different sources. Analysis and prediction using
such data sources provides new challenges for the data mining
and machine learning community.
In a related way, the mining of social data is concerned with
investigating emerging phenomena originating from groups of
individuals and one or more (heterogenous) data sources.
Mining behavioral patterns (e.g., relating to mobility, social
interactions, etc.) in ubiquitous and social environments is an
important up-and-coming area of research focusing on advanced
descriptive and predictive analysis in such distributed and
network-organized contexts.
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 finding behavioral patterns in
ubiquitous and social environments.
GOALS AND AUDIENCE
===
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 state-of-the-art 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.
TOPICS OF INTEREST
===
The topics of the workshop are split roughly into four areas which
include, but are not limited to the following topics:
Ubiquitous Mining:
* Analysis of data from sensors and mobile devices
* Resource-aware algorithms for distributed mining
* Scalable and distributed classification, prediction, and clustering
algorithms
* Mining activity patterns
* Activity recognition
* Mining continuous streams and ubiquitous data
* Online methods for mining temporal, spatial and spatio-temporal data
* Combining data from different sources
Mining Social Data:
* Analysis of social networks and social media
* Mining techniques for social networks and social media
* Algorithms for inferring semantics and meaning from social data
* How social data can be used to mine and create collective intelligence
* Individual and group behavior in social media and social networks
* Analysis of bias in social systems
* Social networks for the collaboration of large communities
* Modeling social behavior
* Novel techniques for mining big data from social media
* Dynamics and evolution patterns of social networks
Ubiquitous and Social Mining
* Personalization and recommendation
* User models and predicting user behavior
* User profiling in ubiquitous and social environments
* Network analysis of social systems
* Discovering social structures and communities
* Mobility mining
* Link prediction
* Analysis of data from crowd-sourcing approaches
Applications:
* Discovering misuse and fraud
* Usage and presentation interfaces for mining and data collection
* Analysis of social and ubiquitous games
* Privacy challenges in ubiquitous and social applications
* Recommenders in ubiquitous and social environments
* Applications of any of the above methods and technologies
We also encourage submissions which relate research results from
other areas to the workshop topics.
SPRINGER BOOK
===
As in the previous years, it is planned to publish revised selected papers
as a volume in the Springer LNCS/LNAI series
WORKSHOP ORGANIZERS
===
* Martin Atzmueller, Knowledge and Data Engineering Group,
University of Kassel, Germany (atzmueller-AT-cs.uni-kassel.de)
* Florian Lemmerich, GESIS - Leibniz Institute for the Social Sciences,
Koeln, Germany (florian.lemmerich-AT-gesis.org)
PROGRAM COMMITTEE
===
Christian Bauckhage, Fraunhofer IAIS, Germany
Martin Becker, University of Wuerzburg, Germany
Albert Bifet, University of Waikato, Germany
Stephan Doerfel, University of Kassel, Germany
Jill Freyne, CSIRO, Australia
Andreas Hotho, University of Wuerzburg, Germany
Mark Kibanov, University of Kassel, Germany
Claudia Mueller-Birn, 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, City University of New York, USA
SUBMISSIONS AND STYLE
===
We invite two types of submissions for this workshop:
* Technical papers in any of the topics of interest of the workshop
(but not limited to them)
* Short position papers in any of the topics of interest of the workshop
(but not limited to them)
Submitted papers will be peer-reviewed and selected on the basis of
these reviews. Accepted papers will be presented at the workshop.
Format requirements for submissions of papers are: Maximum 16
pages, including title page and bibliography for technical
papers. Maximum 8 pages, including title page and bibliography
for short position papers.
All submissions must be entered into the reviewing system:
https://www.easychair.org/conferences/?conf=muse20...
If you have any question please contact the MUSE Organizers. We
recommend to follow the format guidelines of ECML/PKDD (Springer
LNCS), as this will be the required format for accepted papers.
More details can be found on the workshop website:
http://www.kde.cs.uni-kassel.de/ws/muse2015
Important Dates
===
* Paper Submission Deadline: June 22nd, 2015
* Author Notification: July 13th, 2015
* Camera Ready Papers: July 27th, 2016
* Workshop: September 7th, 2015
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Last modified: 2015-05-15 22:53:45