DocumentCode :
3310418
Title :
Name classification in noisy domains
Author :
Frail, Robert P. ; Freedman, Roy S.
Author_Institution :
Common Knowledge, Northport, NY, USA
fYear :
1991
fDate :
9-11 Oct 1991
Firstpage :
16
Lastpage :
22
Abstract :
Many problems in trading and regulation depend on textual data that identifies objects, events, and relationships. In general, these trading and regulatory activities require data from a variety of sources that must be `intelligently integrated´, in order to draw attention to a particular object or group of objects to indicate unusual trading opportunities or to help indicate unusual market behavior for regulators. Text classification techniques have been used for a number of years on Wall Street as significant components of intelligent data integration systems. The authors discuss work on text classification for noisy domains, and discuss how this work has been applied in trading and regulatory systems
Keywords :
classification; information retrieval systems; knowledge based systems; stock markets; word processing; Wall Street; classification techniques; intelligent data integration systems; intelligently integrated; noisy domains; regulatory activities; regulatory systems; text classification; textual data; trading; unusual market behavior; unusual trading opportunities; Data security; Information security; Intelligent systems; Knowledge management; National security; Project management; Regulators; Relational databases; Text categorization; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence Applications on Wall Street, 1991. Proceedings., First International Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-2240-7
Type :
conf
DOI :
10.1109/AIAWS.1991.236579
Filename :
236579
Link To Document :
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