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Motivation

Two major technological evolutions modify our relationship with our environment:

  • Widely available and cheap computer power. Simple objects that surround us are gaining sensors, computational power, and actuators, and are changing from static, into adaptive and reactive systems.
  • The explosion of networks of all kinds offers new possibilities for the development and self-organization of communities.

The new characteristics of data reflect a World in Movement:

  • Time and space. The objects of analysis exist in time and space. Often they are able to move.
  • Dynamic environment. These objects exist in a dynamic and unstable environment, evolving incrementally over time.
  • Information processing capability. The objects are endowed with information processing capabilities.
  • Locality. The objects never see the global picture - they know only their local spatio-temporal environment.
  • Real-Time. The models have to evolve incrementally in correspondence with the evolving environment.
  • Distributed. The object will be able to exchange information with other objects, thus forming a truly distributed environment.

Ubiquitous Data Mining (UDM) uses Data Mining techniques to extract useful knowledge from data with these characteristics. The goal of this workshop is to convene researchers (from both academia and industry) who deal with techniques such as: decision rules, decision trees, association rules, clustering, filtering, learning classifier systems neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques, etc. for UDM and related themes.