posted by system || 2474 views || tracked by 7 users: [display]

MUSE 2012 : Mining Ubiquitous and Social Environments

FacebookTwitterLinkedInGoogle

Link: https://www.kde.cs.uni-kassel.de/ws/muse2012
 
When Sep 24, 2012 - Sep 24, 2012
Where Bristol, UK
Abstract Registration Due Jun 22, 2012
Submission Deadline Jun 29, 2012
Categories    data mining
 

Call For Papers

CALL FOR PAPERS
for the 3rd International ECML/PKDD 2012 Workshop
on


*MINING UBIQUITOUS AND SOCIAL ENVIRONMENTS*
(MUSE 2012)


http://www.kde.cs.uni-kassel.de/ws/muse2012
September 24, 2012 - Bristol, UK
*** Abstract submission: June 22nd, 2012 ***
*** Paper submission deadline: June 29th, 2012 ***
--------------------------------------------------------------------------

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. Additionally, the upcoming social semantic
web also integrates the user interactions in social networking
environments. Mining in ubiquitous and social environments is
thus an emerging area of research focusing on advanced systems
for data mining in such distributed and network-organized
systems. It also integrates some related technologies such as
activity recognition, Web 2.0 mining, privacy issues and
privacy-preserving mining, predicting user behavior, etc.

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 are in general 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. As there is
only minimal coordination, these sources can overlap or diverge
in any possible way. 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.

GOALS AND AUDIENCE
==================
The goal of this workshop is to promote an interdisciplinary
forum for researchers working in the fields of ubiquitous
computing, social semantic web, Web 2.0, and social networks
which are interested in utilizing data mining in an ubiquitous
setting. The workshop seeks for contributions applying
state-of-the-art mining algorithms on ubiquitous and social
data. Papers focusing on the intersection 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
* Activity recognition
* Mining continuous streams and ubiquitous data
* Online methods for mining temporal, spatial and spatio-temporal data
* Combining data from different sources
* Sensor data preprocessing, transformation, and space-time sampling techniques
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
* Privacy and security issues in social data
* How social data can be used to mine and create collective intelligence
* Individual and group behavior in social media and social networks
* Social networks for the collaboration of large communities
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
* 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
* 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@cs.uni-kassel.de)
* Andreas Hotho, Data Mining and Information Retrieval Group,
University of Wuerzburg, Germany (hotho@informatik.uni-wuerzburg.de)

PROGRAM COMMITTEE
==================
* Ulf Brefeld, Yahoo Research, Spain
* Ricardo Cachucho, Leiden University, The Netherlands
* Michelangelo Ceci, University of Bari, Italy
* Padraig Cunningham, University College Dublin, Ireland
* Daniel Gayo-Avello, University of Oviedo, Spain
* Ido Guy, IBM Research, USA
* Kristian Kersting, University of Bonn, Germany
* Matthias Klusch, DFKI GmbH, Germany
* Claudia M?ller-Birn, FU Berlin, Germany
* Alexandre Passant, DERI, Ireland
* Giovanni Semeraro, University of Bari, Italy
* Maarten van Someren, University of Amsterdam, The Netherlands
* Markus Strohmaier, TU Graz, Austria
* Ugo Vespier, Leiden University, The Netherlands



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=muse2012

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/muse2012

Important Dates
===============
* Abstract Submission: June 22nd
* Paper Submission Deadline: June 29th, 2012
* Author Notification: July 20th, 2012
* Camera Ready Papers: August 3rd, 2012

Related Resources

ICDM 2020   20th IEEE International Conference on Data Mining
NLPUH - PUC 2020   Natural Language Processing in Ubiquitous Healthcare
ECML PKDD 2020   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
ASONAM 2020   The 2020 IEEE/ACM International Conference on. Advances in Social Networks Analysis and Mining
IoTMO 2020   Advanced Internet of Things for Medicine and Others - IoTMO 2020 The Internet of Things and Services
ICDM 2020   Call for Short&Industry Papers / 20th Industrial Conference on Data Mining ICDM 2020
Scopus-PRIS 2020   International Conference on Pattern Recognition and Intelligent Systems(PRIS 2020)
EMNLP 2020   Conference on Empirical Methods in Natural Language Processing
MoWiN 2020   9th International Conference on Mobile & Wireless Networks
CDKP 2020   9th International Conference on Data Mining & Knowledge Management Process