-------- Weitergeleitete Nachricht -------- Betreff: [WI] CfP: MUSE 2015 - 6th International ECML/PKDD 2015 Workshop on Mining Ubiquitous and Social Environments Datum: Thu, 14 May 2015 00:28:10 +0200 Von: Martin Atzmueller atzmueller@cs.uni-kassel.de An: ak-kd-list@lists.uni-karlsruhe.de, fg-db@informatik.uni-rostock.de, kdml@cs.uni-kassel.de, wi@aifb.uni-karlsruhe.de
** Please forward to anyone who might be interested ** --------------------------------------------------------------------------
CALL FOR PAPERS for the 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@cs.uni-kassel.de) * Florian Lemmerich, GESIS - Leibniz Institute for the Social Sciences, Koeln, Germany (florian.lemmerich@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=muse2015
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