Title :
CBR case retrieval model research in business financial distress warning based on gray relation
Author :
Shen Qi ; Chen Aiping
Author_Institution :
Jiangsu Inf. Anal. Eng. Lab., Nanjing, China
Abstract :
Similar case retrieval ability is a key technology in CBR(Case Based Reasoning) system. In order to improve the case retrieval efficiency in business financial distress warning(FDW) system, a CBR case retrieval model based on gray relation was proposed, applying the gray relational analysis in case based reasoning for business FDW which improved the deficiency of distance measurement. Moreover, taking into account the different importance of case features in predicting financial distress, a weight vector was defined to solve the influence coming from nor-crucial features. Empirical results proves that this method can effectively improve the case retrieval efficiency of the target enterprise in business FDW system.
Keywords :
business data processing; case-based reasoning; feature extraction; financial data processing; financial management; grey systems; information retrieval; CBR case retrieval model research; business FDW system; business financial distress warning; case based reasoning system; case features; case retrieval efficiency; distance measurement; enterprise; financial distress prediction; gray relational analysis; retrieval ability; weight vector; Analytical models; Artificial intelligence; Business; Cognition; Computers; Neural networks; Robots; Business financial distress warning; Case based reasoning; Case retrieval; Gray relation; K-nearest neighbors;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219224
