DocumentCode :
2716629
Title :
mTRACK — Monitoring time-varying relations in approximately categorised knowledge
Author :
Martin, Trevor ; Shen, Yun
Author_Institution :
Artificial Intell. Group, Univ. of Bristol, Bristol, UK
fYear :
2009
fDate :
8-10 July 2009
Firstpage :
1
Lastpage :
8
Abstract :
Recent initiatives in defence related information systems have emphasised the need to bring together information from multiple sources and fuse it into a form suitable for decision makers. This paper outlines a four stage system for fusing unstructured and semi-structured text and numerical data by extraction of entities and relations, identification of duplicate entities, organisation into the most appropriate hierarchical categories and determination of relations between fuzzy categories. The novel contribution of this paper is in the final stage of the process, where we determine associations between fuzzy categories and identify strong and/or unusual levels of association as well as changes over time. A demonstrator application shows how information on terrorist incidents from multiple sources can be integrated and monitored.
Keywords :
decision making; information systems; query processing; sensor fusion; approximately categorised knowledge; decision making; defence related information systems; duplicate entities; fuzzy categories; hierarchical categories; mTRACK; numerical data fusion; text fusion; time-varying relations; Association rules; Computational intelligence; Data mining; Data security; Humans; Information systems; Monitoring; National electric code; Project management; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Security and Defense Applications, 2009. CISDA 2009. IEEE Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-3763-4
Electronic_ISBN :
978-1-4244-3764-1
Type :
conf
DOI :
10.1109/CISDA.2009.5356563
Filename :
5356563
Link To Document :
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