DocumentCode :
1965254
Title :
Helping intelligence analysts detect threats in overflowing, changing and incomplete information
Author :
Thomere, Jerome ; Harrison, Ian ; Lowrance, John ; Rodriguez, Andres ; Ruspini, Enrique ; Wolverton, Michael
Author_Institution :
Artificial Intelligence Center, SRI Int., Menlo Park, CA, USA
fYear :
2004
fDate :
21-22 July 2004
Firstpage :
39
Lastpage :
45
Abstract :
An important role of intelligence organizations is to be able to identify and predict threats within a vast quantity of imprecise and noisy information. We describe the concept and function of our pattern-matching architecture, LAW (Link Analysis Workbench). This system is based upon two main ideas. The first idea is that both the data and the threats can be described in term of graphs of entities and events linked together with semantic relationships. Therefore, graph-based pattern matching techniques can be used to identify threats. The second idea is that analysts constitute an essential part of the system; LAW is designed to handle a lot of interaction with the user, particularly to help in authoring and revising patterns, by allowing analysts to understand the matching process and results.
Keywords :
data analysis; graph theory; pattern matching; relational databases; security; changing information; graph-based pattern matching techniques; graph-edit distance; incomplete information; intelligence analysts; intelligence organizations; link analysis workbench; noisy information; ontologies; overflowing information; pattern-matching architecture; relational data; semantic relationships; threat detection; threat identification; Discrete event simulation; Information analysis; Information retrieval; Observability; Ontologies; Pattern analysis; Pattern matching; Relational databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN :
0-7803-8381-8
Type :
conf
DOI :
10.1109/CIHSPS.2004.1360205
Filename :
1360205
Link To Document :
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