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

• Record Nr.: UNISA996465607203316
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
• ISBN: 1-280-38628-2; 9786613564207; 3-642-12519-0
• Edizione: [1st ed. 2010.]
• Descrizione fisica: 1 online resource (IX, 227 p. 110 illus.)
• Collana: Information Systems and Applications, incl. Internet/Web, and HCI ; ; 5840
• Disciplina: 025.04
• Soggetti: 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; Congressos; Llibres electrònics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• 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.