Ubiquitous Knowledge Discovery

Challenges, Techniques, Applications

  • Michael May
  • Lorenza Saitta

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6202)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 6202)

Table of contents

  1. Front Matter
  2. A Blueprint for Ubiquitous Knowledge Discovery

    1. Front Matter
      Pages 1-1
    2. Michael May, Lorenza Saitta
      Pages 3-18
    3. Assaf Schuster, Ran Wolff
      Pages 19-39
    4. João Gama, Antoine Cornuéjols
      Pages 40-60
    5. Andreas Hotho, Rasmus Ulslev Pedersen, Michael Wurst
      Pages 61-74
    6. Fosca Giannotti, Yücel Saygin
      Pages 75-89
    7. Bettina Berendt, Ernestina Menasalvas
      Pages 90-107
    8. Koen Vanhoof, Ina Lauth
      Pages 108-125
  3. Case Studies

    1. Front Matter
      Pages 127-127
    2. Antoine Cornuéjols
      Pages 129-147
    3. Milton Severo, João Gama
      Pages 148-162
    4. Izchak Sharfman, Assaf Schuster, Daniel Keren
      Pages 163-186
    5. MineFleetOpen image in new window: The Vehicle Data Stream Mining System for Ubiquitous Environments
      Hillol Kargupta, Michael Gilligan, Vasundhara Puttagunta, Kakali Sarkar, Martin Klein, Nick Lenzi et al.
      Pages 235-254
  4. Back Matter

About this book


Knowledge discovery in ubiquitous environments 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, peer-to-peer networks, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others. This state-of-the-art survey is the outcome of a large number of workshops, summer schools, tutorials and dissemination events organized by KDubiq (Knowledge Discovery in Ubiquitous Environments), a networking project funded by the European Commission to bring together researchers and practitioners of this emerging community. It provides in its first part a conceptual foundation for the new field of ubiquitous knowledge discovery - highlighting challenges and problems, and proposing future directions in the area of 'smart', 'adaptive', and 'intelligent' learning. The second part of this volume contains selected approaches to ubiquitous knowledge discovery and treats specific aspects in detail. The contributions have been carefully selected to provide illustrations and in-depth discussions for some of the major findings of Part I.


Clustering KDubiq algorithmic learning association rule mining classification cognition data mining data stream mining embedded systems intelligent systems knowledge discovery learning machine learning micro information systems modeling

Editors and affiliations

  • Michael May
    • 1
  • Lorenza Saitta
    • 2
  1. 1.Fraunhofer IAIS, Schloss BirlinghovenSankt AugustinGermany
  2. 2.Dipartimento di InformaticaUniversità del Piemonte Orientale Amedeo AvogadroAlessandriaItaly

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-16391-3
  • Online ISBN 978-3-642-16392-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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