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| Artikel-Nr.: 5667A-9783642125188 Herst.-Nr.: 9783642125188 EAN/GTIN: 9783642125188 |
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 | 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. Weitere Informationen:  |  | Author: | Mohamed Medhat Gaber; Ranga Raju Vatsavai; Olufemi A. Omitaomu; João Gama; Nitesh V. Chawla; Auroop R. Ganguly | Verlag: | Springer Berlin | Sprache: | eng |
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 | Weitere Suchbegriffe: allgemeine Informatikbücher - englischsprachig, allgemeine informatikbücher - englischsprachig, Data Mining (EDV), Data Mining; Disaster Management; Online; Remote Sensors; knowledge discovery; sensor mining; sensor networks, data mining, disaster management, knowledge discovery, online, remote sensors, sensor mining, sensor networks |
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