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Software risk management is crucial for the success of software project development. The existing literature has models for risk management, but is too complex to be used in practice. The information in the existing studies is scattered over different articles which makes it difficult to find relevant knowledge to establish relationship between risk factors and mitigations. This paper presents a novel model which identifies the relationship between risk factors and mitigations automatically by using intelligent Decision Support System (DSS). The proposed model has four steps. Firstly, the input of the system has been designed where risk factors and mitigations have been inputted into it. Secondly, rule based machine learning approach has been used for mining of associations between risks and mitigations. Thirdly, Case Based Reasoning (CBR) approach has been used to determine the previous cases as rules. Finally …