Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Activity monitoring: noticing interesting changes in behavior
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
Data Mining and Knowledge Discovery
A Dynamic Manifestation Approach for Providing Universal Access to Digital Library Objects
IEEE Transactions on Knowledge and Data Engineering
Mining Partially Periodic Event Patterns with Unknown Periods
Proceedings of the 17th International Conference on Data Engineering
Mining Mutually Dependent Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Spatial Data Mining: A Database Approach
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Frequent term-based text clustering
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Self-manifestation of composite multimedia objects to satisfy security constraints
Proceedings of the 2003 ACM symposium on Applied computing
Neighborhood based detection of anomalies in high dimensional spatio-temporal sensor datasets
Proceedings of the 2004 ACM symposium on Applied computing
dg.o '04 Proceedings of the 2004 annual national conference on Digital government research
Discovering actionable patterns in event data
IBM Systems Journal
Agency interoperation for effective data mining in border control and homeland security applications
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Survey of data management and analysis in disaster situations
Journal of Systems and Software
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Alert management plays a critical role in many application domains including homeland security and natural disaster management, to allow timely and well-informed decisions. The major challenge faced by these systems is that the number of incoming alarms is overwhelming and some of the alarms are false positives. In this paper, we present an alert management system (AMS) that generates meaningful alerts from alarms received from different sensors. The alert generation module of our system (i) flags and eliminates potential false positives by characterizing the region into uniformly behaving neighborhoods, (ii) generates aggregated alerts from the alarms by employing density based clustering techniques and identifying the overlap among clusters, and (iii) identifies the dynamic flow of the alerts by integrating scientific models that characterize the behavior of sensor parameters. Once the alerts are generated our customized dissemination module disperses the alerts on the need-to-know basis to the individuals and agencies involved. This module adheres to the National Incident Management System (NIMS) and the National Response plan (NRP) protocols. To implement these protocols, we utilize the Common Alerting Protocol (CAP), which is an XML nonproprietary data interchange format. Finally, our GIS module displays the alerts through a user-friendly interface.