Knowledge Discovery from Sensor Data

This volume contains extended papers from Sensor-KDD 2008, the Second - ternational Workshop on Knowledge Discovery from Sensor Data. The second Sensor-KDDworkshopwasheldinLasVegasonAugust24,2008,inconjunction with the 14th ACM SIGKDD InternationalConference on KnowledgeDiscovery and Data Mining. Wide-area sensor infrastructures, remote sensors, and wireless sensor n- works, RFIDs, yield massive volumes of disparate, dynamic, and geographically distributeddata.Assuchsensorsarebecomingubiquitous,asetofbroadrequi- ments is beginning to emerge across high-priority applications including dis- ter preparedness and management, adaptability to climate change, national or homelandsecurity,andthe managementofcriticalinfrastructures.Therawdata from sensors need to be e?ciently managed and transformed to usable infor- tion through data fusion, which in turn must be converted to predictive insights via knowledge discovery, ultimately facilitating automated or human-induced tactical decisions or strategic policy based on decision sciences and decision s- port systems. The expected ubiquity of sensors in the near future, combined with the cr- ical roles they are expected to play in high-priority application solutions, points to an era of unprecedented growth and opportunities. The main motivation for the Sensor-KDD series of workshops stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate coll- oration and dialog between academia, government, and industrial stakeho- ers. This is clearly re?ected in the successful organization of the ?rst workshop alongwiththe ACMKDD-2007conference,whichwasattendedbymorethanseventyregistered participants, and resulted in an edited book (CRC Press, ISBN-9781420082326, 2008), and a special issue in the Intelligent Data Analysis journal (Volume 13, Number 3, 2009).

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Klappentext

This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Inhalt
Data Mining for Diagnostic Debugging in Sensor Networks: Preliminary Evidence and Lessons Learned.- Monitoring Incremental Histogram Distribution for Change Detection in Data Streams.- Situation-Aware Adaptive Visualization for Sensory Data Stream Mining.- Unsupervised Plan Detection with Factor Graphs.- WiFi Miner: An Online Apriori-Infrequent Based Wireless Intrusion System.- Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set.- Spatio-temporal Outlier Detection in Precipitation Data.- Large-Scale Inference of Network-Service Disruption upon Natural Disasters.- An Adaptive Sensor Mining Framework for Pervasive Computing Applications.- A Simple Dense Pixel Visualization for Mobile Sensor Data Mining.- Incremental Anomaly Detection Approach for Characterizing Unusual Profiles.- Spatiotemporal Neighborhood Discovery for Sensor Data.