Knowledge Discovery from Sensor Data

Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers

240 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: Lecture Notes in Computer Science
• Themen: Informatik und Informationstechnologie Datenbanken / Datenmanagement Data Warehousing
• ISBN: 9783642125188
• Sprache: Englisch
• Erscheinungsdatum: 14.04.2010
• Größe: 235 x 155 mm
• Verlag: Springer Spektrum
• Herausgegeben von: Olufemi A. Omitaomu, João Gama, Auroop R. Ganguly, Mohamed Medhat Gaber, Nitesh V. Chawla, Ranga Raju Vatsavai