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Knowledge Discovery from Sensor Data [[electronic resource] ] : Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers / / edited by Mohamed Medhat Gaber, Ranga Raju Vatsavai, Olufemi A. Omitaomu, João Gama, Nitesh V. Chawla, Auroop R. Ganguly
Knowledge Discovery from Sensor Data [[electronic resource] ] : Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers / / edited by Mohamed Medhat Gaber, Ranga Raju Vatsavai, Olufemi A. Omitaomu, João Gama, Nitesh V. Chawla, Auroop R. Ganguly
Edizione [1st ed. 2010.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Descrizione fisica 1 online resource (IX, 227 p. 110 illus.)
Disciplina 025.04
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Xarxes de sensors
Intel·ligència artificial
Information storage and retrieval
Computer communication systems
Database management
Data mining
Pattern recognition
Information Storage and Retrieval
Computer Communication Networks
Database Management
Data Mining and Knowledge Discovery
Pattern Recognition
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 1-280-38628-2
9786613564207
3-642-12519-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996465607203316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Proceedings of the fifth International Workshop on Knowledge Discovery from Sensor Data (SensorKDD'11) : August 21, 2011 San Diego, CA
Proceedings of the fifth International Workshop on Knowledge Discovery from Sensor Data (SensorKDD'11) : August 21, 2011 San Diego, CA
Autore Chandola Varun
Pubbl/distr/stampa [Place of publication not identified], : ACM, 2011
Descrizione fisica 1 online resource (69 pages)
Collana ACM Conferences
Soggetto topico Engineering & Applied Sciences
Computer Science
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti KDD '11 the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA - August 21 - 24, 2011
Record Nr. UNINA-9910376506903321
Chandola Varun  
[Place of publication not identified], : ACM, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
Autore Omitaomu Olufemi A
Pubbl/distr/stampa [Place of publication not identified], : Association for Computing Machinery, 2009
Descrizione fisica 1 online resource (150 p.;)
Collana ACM Conferences
Soggetto topico Information Technology - Computer Science (Hardware & Networks)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti SensorKDD '09
Record Nr. UNINA-9910375809903321
Omitaomu Olufemi A  
[Place of publication not identified], : Association for Computing Machinery, 2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
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