Title : 
Case-Based Reasoning Algorithm Based on Qualitative Causality
         
        
            Author : 
Zhile Liu ; Lingfei Fu ; Yanchun Zhou
         
        
            Author_Institution : 
Sch. of Bus., Ningbo Univ., Ningbo, China
         
        
        
        
        
        
            Abstract : 
With the limitation of low predictive performance and poor reliability in current case-based reasoning method, this paper proposes a case-based reasoning algorithm based on qualitative causality (CBR-QC). On the basis of traditional quantitative retrieval method, it introduces relevant knowledge about qualitative reasoning, describes the case qualitatively with qualitative method, constructs qualitative equations, and then gets case groups with requirements through qualitative retrieval. Euclidean distance similarity computation method and KNN method are applicable in this article to retrieve quantitatively similar cases from retrieved qualitatively similar cases, finally get prediction values through adapting the retrieved cases.
         
        
            Keywords : 
case-based reasoning; CBR-QC; Euclidean distance similarity computation method; KNN method; case-based reasoning algorithm; low predictive performance; qualitative causality; qualitative reasoning; qualitative retrieval; quantitative retrieval method; Business; Cognition; Educational institutions; Equations; Euclidean distance; Mathematical model; Predictive models; case-based reasoning; human intelligence; predictive model; qualitative causality;
         
        
        
        
            Conference_Titel : 
Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4799-5371-4
         
        
        
            DOI : 
10.1109/CSO.2014.102