TY  - BOOK
AU  - Gaber,Mohamed Medhat
AU  - Vatsavai,Ranga Raju
AU  - Omitaomu,Olufemi A.
AU  - Gama,João
AU  - Chawla,Nitesh V.
AU  - Ganguly,Auroop R.
ED  - SpringerLink (Online service)
TI  - Knowledge Discovery from Sensor Data: Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers 
T2  - Lecture Notes in Computer Science,
SN  - 9783642125195
AV  - QA75.5-76.95 
U1  - 025.04 23
PY  - 2010///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Computer Communication Networks
KW  - Database management
KW  - Data mining
KW  - Information storage and retrieval systems
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Information Storage and Retrieval
KW  - Database Management
KW  - Data Mining and Knowledge Discovery
KW  - Pattern Recognition
N1  - 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
N2  - 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 (http://www.ornl.gov/sci/knowledgediscovery/SensorKDD-2007/)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)
UR  - http://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-12519-5
ER  -