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  • Conference proceedings
  • © 2010

Knowledge Discovery from Sensor Data

Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers

Editors:

  1. Mohamed Medhat Gaber

    1. Centre for Distributed Systems and Software Engineering, Monash University, Melbourne, Australia

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  2. Ranga Raju Vatsavai

    1. Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, USA

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  3. Olufemi A. Omitaomu

    1. Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, USA

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  4. João Gama

    1. Faculty of Economics, LIAAD-INESC Porto, University of Porto, Porto, Portugal

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  5. Nitesh V. Chawla

    1. Computer Science and Engineering Department, University of Notre Dame, Notre Dame, USA

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  6. Auroop R. Ganguly

    1. Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5840)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Conference series link(s): Sensor-KDD: International Workshop on Knowledge Discovery from Sensor Data

Conference proceedings info: Sensor-KDD 2008.

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Table of contents (12 papers)

  1. Front Matter

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  2. Data Mining for Diagnostic Debugging in Sensor Networks: Preliminary Evidence and Lessons Learned

    • Tarek Abdelzaher, Mohammad Khan, Hieu Le, Hossein Ahmadi, Jiawei Han
    Pages 1-24

  3. Monitoring Incremental Histogram Distribution for Change Detection in Data Streams

    • Raquel Sebastião, João Gama, Pedro Pereira Rodrigues, João Bernardes
    Pages 25-42

  4. Situation-Aware Adaptive Visualization for Sensory Data Stream Mining

    • Pari Delir Haghighi, Brett Gillick, Shonali Krishnaswamy, Mohamed Medhat Gaber, Arkady Zaslavsky
    Pages 43-58

  5. Unsupervised Plan Detection with Factor Graphs

    • George B. Davis, Jamie Olson, Kathleen M. Carley
    Pages 59-75

  6. WiFi Miner: An Online Apriori-Infrequent Based Wireless Intrusion System

    • Ahmedur Rahman, C. I. Ezeife, A. K. Aggarwal
    Pages 76-93

  7. Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set

    • Jon Hutchins, Alexander Ihler, Padhraic Smyth
    Pages 94-114

  8. Spatio-temporal Outlier Detection in Precipitation Data

    • Elizabeth Wu, Wei Liu, Sanjay Chawla
    Pages 115-133

  9. Large-Scale Inference of Network-Service Disruption upon Natural Disasters

    • Supaporn Erjongmanee, Chuanyi Ji, Jere Stokely, Neale Hightower
    Pages 134-153

  11. A Simple Dense Pixel Visualization for Mobile Sensor Data Mining

    • Pedro Pereira Rodrigues, João Gama
    Pages 175-189

  12. Incremental Anomaly Detection Approach for Characterizing Unusual Profiles

    • Yi Fang, Olufemi A. Omitaomu, Auroop R. Ganguly
    Pages 190-202

  13. Spatiotemporal Neighborhood Discovery for Sensor Data

    • Michael P. McGuire, Vandana P. Janeja, Aryya Gangopadhyay
    Pages 203-225

  14. Back Matter

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Other Volumes

  1. Knowledge Discovery from Sensor Data

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Keywords

  • data mining
  • disaster management
  • knowledge discovery
  • online
  • remote sensors
  • sensor mining
  • sensor networks
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Editors and Affiliations

  • Centre for Distributed Systems and Software Engineering, Monash University, Melbourne, Australia

    Mohamed Medhat Gaber

  • Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, USA

    Ranga Raju Vatsavai, Olufemi A. Omitaomu, Auroop R. Ganguly

  • Faculty of Economics, LIAAD-INESC Porto, University of Porto, Porto, Portugal

    João Gama

  • Computer Science and Engineering Department, University of Notre Dame, Notre Dame, USA

    Nitesh V. Chawla

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Bibliographic Information

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Access via your institution
eBook USD 64.99
Price excludes VAT (USA)
  • ISBN: 978-3-642-12519-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 84.99
Price excludes VAT (USA)
Learn about institutional subscriptions