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                                       Details for article 56 of 82 found articles
 
 
  KNOWLEDGE DISCOVERY IN INTERNATIONAL CONFLICT DATABASES
 
 
Title: KNOWLEDGE DISCOVERY IN INTERNATIONAL CONFLICT DATABASES
Author: FURNKRANZ, JOHANNES
PETRAK, JOHANN
TRAPPL, ROBERT
Appeared in: Applied artificial intelligence
Paging: Volume 11 (1997) nr. 2 pages 91-118
Year: 1997-03-01
Contents: Artificial intelligence (AI) is heavily supported by military institutions, while practically no effort goes into the investigation of possible contributions of AI to the avoidance and termination of crises and wars. This article takes a first step in this direction by investigating the use of machine learning techniques for discovering knowledge in international conflict and conflict management databases. We have applied similarity-based case retrieval to the KOSIMO database of international conflicts. Furthermore, we present results of analyzing the CONFMAN database of successful and unsuccessful conflict management attempts with an inductive decision tree learning algorithm. The latter approach seems to be particularly promising, as conflict management events apparently are more repetitive and thus better suited for machine-aided analysis.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 56 of 82 found articles
 
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