First Ubiquitous Knowledge Discovery Workshop (UKD08)
September 19, 2008 in Antwerp, Belgium
in conjuction with ECML/PKDD 2008 Conferences


UKD Technical Description

Over the last years, ubiquitous computing has started to create a new world of small, heterogeneous, and distributed devices that have the ability to sense, to communicate and interact in ad hoc or sensor networks and peer2peer systems. These large scale distributed systems have in many cases to interact in real-time with their users.
Knowledge Discovery in ubiquitous environments (KDubiq) is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. It aims to provide a unifying framework for systematically investigating the mutual dependencies of otherwise quite unrelated technologies employed in building next-generation intelligent systems: machine learning, data mining, sensor networks, grids, P2P, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others.
In a fully ubiquitous setting, the learning typically takes place in situ, inside the small devices. Its characteristics are quite different from the current mainstream data mining and machine learning. Instead of offline-learning in a batch setting, sequential learning, anytime learning, real-time learning, online learning etc. under real-time constraints from ubiquitous and distributed data is needed. Instead of learning from stationary distributions, concept drift is the rule rather than the exception. Instead of large stand-alone workstations, learning takes place in unreliable, highly resource constrained environments in terms of battery power and bandwidth.
The goal of this workshop is to promote an interdisciplinary forum for researchers who deal with sequential learning, anytime learning, real-time learning, online learning, etc. from ubiquitous and distributed data. Distributed Learning from Data Streams is a recent and increasing research area with challenging applications and contributions from fields like Data Bases, Data Mining, Machine Learning, and Statistics.

UKD Topics


The workshop will address all topics of ubiquitous knowledge discovery, including:

  • Parallel and distributed mining in Peer-to-Peer networks, sensor networks and grids
  • Activity recognition
  • Sensor data preprocessing, transformation, and space-time sampling techniques
  • Online methods for mining temporal, spatial and spatio-temporal data
  • Scalable and distributed classification, prediction, and clustering algorithms
  • Mining continuous streams and ubiquitous data
  • Resource-aware algorithms for distributed mining
  • Ubiquitous user modeling
  • Change Detection Algorithms
  • Visualization Techniques for Distributed Data Streams
  • Applications of ubiquitous knowledge discovery in various domains, including telecommunications, environment, Earth observation and monitoring, urban planning, web/road traffic, etc.


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Workshop Chairs:

  1. Michael May (Fraunhofer IAIS, Germany)
  2. Antoine Cornéjols (LRI, France)
  3. Joao Gama (Univ. Porto, Portugal)
  4. Rasmus Pedersen (Copenhagen Business School, Denmark)
  5. Koen Vanhoof (Uni. Hasselt, Belgium)

Program Committee

  • Bettina Berendt, Univ. Leuven, Belgium
  • Fosca Giannotti, Pisa KDD-Lab, Italy
  • Andreas Hotho, Univ. Kassel, Germany
  • Hillol Kargupta, Univ. Maryland, Baltimore County, USA
  • Donato Malerba, Univ. Bari, Italy
  • Ernestina Menasalvas, Univ. Madrid, Spain
  • Dino Pedreschi, Univ. Pisa, Italy
  • Lorenza Saitta, Univ. Piemonte, Italy
  • Yücel Saygin, Sabanci Univ., Turkey
  • Albrecht Schmidt, Univ. Duisburg-Essen, Germany
  • Assaf Schuster, Technion, Israel
  • Maarten van Someren, Univ. Amsterdam, The Netherlands

Workshop Structure and Attendance

The workshop aims to be a highly communicative meeting place for researchers working on similar topics, but coming from different communities. In order to achieve these goals, the workshop will consist of two invited talks, followed by short presentations and longer discussions. A panel session will be organized as closing event of the workshop.
All workshop participants must also register for the main ECML/PKDD conference. Workshop attendance will be limited to registered participants.