Knowledge Discovery from Sensor Data
Gaber, Mohamed Medhat.
Knowledge Discovery from Sensor Data Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers / [recurso electrónico] : edited by Mohamed Medhat Gaber, Ranga Raju Vatsavai, Olufemi A. Omitaomu, João Gama, Nitesh V. Chawla, Auroop R. Ganguly. - IX, 227p. 110 illus. online resource. - Lecture Notes in Computer Science, 5840 0302-9743 ; . - Lecture Notes in Computer Science, 5840 .
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.
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).
9783642125195
Computer science.
Computer Communication Networks.
Database management.
Data mining.
Information storage and retrieval systems.
Optical pattern recognition.
Computer Science.
Information Storage and Retrieval.
Computer Communication Networks.
Database Management.
Data Mining and Knowledge Discovery.
Pattern Recognition.
QA75.5-76.95
025.04
Knowledge Discovery from Sensor Data Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers / [recurso electrónico] : edited by Mohamed Medhat Gaber, Ranga Raju Vatsavai, Olufemi A. Omitaomu, João Gama, Nitesh V. Chawla, Auroop R. Ganguly. - IX, 227p. 110 illus. online resource. - Lecture Notes in Computer Science, 5840 0302-9743 ; . - Lecture Notes in Computer Science, 5840 .
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.
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).
9783642125195
Computer science.
Computer Communication Networks.
Database management.
Data mining.
Information storage and retrieval systems.
Optical pattern recognition.
Computer Science.
Information Storage and Retrieval.
Computer Communication Networks.
Database Management.
Data Mining and Knowledge Discovery.
Pattern Recognition.
QA75.5-76.95
025.04
