Paper Info
Title
Anomaly Detection in Emergency Call Data The First Step to the Intelligent Emergency Call System Management
Abstract
A collaborative Emergency call taking information system in the Czech Republic processes calls on the European 112 emergency number. Amounts of various incident records are stored in its databases. The data can be used for mining spatial and temporal anomalies. When such an anomalous situation is detected so that the system could suffer from local or temporal performance decrease, either a human, or an automatic management module could take measures to reconfigure the system traffic and balance its load. In this paper we describe a method of knowledge discovery and visualization with respect to the emergency call taking information system database characteristics. The method is based on Kohonen Self Organizing Map (SOM) algorithm. Transformations of categorical attributes into numeric values are proposed to prepare training set appropriate for successful SOM generation.
Year
DOI
Venue
2009
10.1109/INCOS.2009.35
INCoS
Keywords
Field
DocType
intelligent emergency call system,information system database characteristic,temporal anomaly,system traffic,temporal performance decrease,successful som generation,czech republic,information system,kohonen self organizing map,first step,emergency number,anomaly detection,anomalous situation,emergency call data,load balancing,data clustering,databases,clustering algorithms,temporal databases,groupware,system management,classification algorithms,self organizing map,knowledge discovery,data mining,resource allocation
Information system,Data mining,Anomaly detection,Computer science,Self-organizing map,Temporal database,Call management,Knowledge extraction,Systems management,Cluster analysis
Conference
Citations 
PageRank 
References 
4
0.59
5
Authors
2
Name
Order
Citations
PageRank
Petr Klement191.81
Václav Snášel23710.63