News

2012-09-23: The proceedings are now online.

2012-09-10: The program is now online.

2012-04-05: The web page for the workshop is now online.

Important dates

Submission deadlines

  • Abstract Submission: Friday, June 22nd, 2012
  • Paper Submission: Friday, June 29th, 2012
  • Acceptance Notification: Friday, July 20th, 2012
  • Paper Final Version Due: Friday, August 3rd, 2012
  • Workshop: Monday, Sep 24th, 2012

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. 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, social web 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. 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.

The goal of this workshop is to promote an interdisciplinary forum for researchers working in the fields of ubiquitous computing, 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
    • 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, Kassel University, Germany
    ( )
  • Andreas Hotho, Data Mining and Information Retrieval Group, University of Wuerzburg, Germany
    ( )

Proceedings

Download the MUSE proceedings here.

Program

  • 9:00-10:30: Session 1
    • 9:00 - 9:15: Welcome and Introduction
    • 9:15 - 10:30: Invited Talk - Daqing Zhang: Extracting Social and Community Intelligence by Mining Large Scale Digital Footprints
      As a result of the recent explosion of sensor-equipped mobile phones, the phenomenal growth of Internet and social network services, the broader use of the Global Positioning System (GPS) in all types of public transportation, and the extensive deployment of sensor network and WiFi in both indoor and outdoor environments, the digital footprints left by people while interacting with cyber-physical spaces are accumulating with an unprecedented speed and scale. The technology trend towards pervasive sensing and computing is making ”social and community intelligence (SCI)”, a new research area take shape, that aims at mining the “digital footprints” to reveal the human behavior patterns and community dynamics.
      It is believed that SCI is pushing the research in context-aware computing to a new territory. In this talk, I would like to introduce this emerging research area, present the research background and the evolution of SCI, define the general system framework, discuss the major applications and future research issues of SCI. In particular, I will present our recent work in mining the large scale taxis GPS traces for innovative smart city services and mining the large scale social media data (Foursquare) for community detection and recommendation.
  • 10:30 - 11:00: Coffee break

  • 11:00 - 12:15: Session 2
  • 12:15 - 13:45: Lunch

  • 13:45 - 16:00: Session 3
    • 13:45 - 14:05: Annalisa Appice, Donato Malerba and Antonietta Lanza: Geographically-Aware Mining of AIS Messages to Track Ship Itineraries
    • 14:05 - 14:40: John Vogel and David Tresner-Kirsch: Robust Language Identi cation in Short, Noisy Texts: Improvements to LIGA
    • 14:40 - 15:15: Ursula Redmond, Martin Harrigan and Padraig Cunningham: Identifying Time-Respecting Subgraphs in Temporal Networks
    • 15:15 - 16:00: Discussion + Closing

Program Committee

  • Ulf Brefeld, University of Bonn, Germany
  • 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 Müller-Birn, FU Berlin, Germany
  • Alexandre Passant, DERI, Ireland
  • Claudio Sartori, University of Bologna, Italy
  • 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

Submission and Proceedings

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:

We recommend to follow the format guidelines of ECML/PKDD (Springer LNCS), as this will be the required format for accepted papers (cf. instructions).