MUSE 2011 - Workshop Mining Ubiquitous and Social Environments (MUSE 2011)

Website www.ecmlpkdd2011.org | Edit Freely

Category MUSE 2011

Deadline: June 07, 2011 | Date: September 09, 2011-September 11, 2011

Venue/Country: Athens, Greece

Updated: 2011-04-16 14:08:49 (GMT+9)

Call For Papers - CFP

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.

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 three areas which include, but are not limited to the following topics:

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

User behavior:

Personalization and recommendation

User models and predicting user behavior

User profiling in ubiquitous and social environments

Mining continuous streams and ubiquitous data

Network analysis of social systems

Discovering social structures and communities

Applications:

Discovering misuse and fraud

Usage and presentation interfaces for mining and data collection

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 year, 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

( atzmuellercs.uni-kassel.de )

Andreas Hotho, Data Mining and Information Retrieval Group, University of Wuerzburg, Germany

( hothocs.uni-kassel.de )