2014Unpublished venueRequires access

Study of Different Risk Management Model and Risk Knowledge acquisition with WEKA

Kiranpreet Kaur, Amandeep Kaur, Rupinder Kaur

Open publisher page 2 citations

Abstract

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In this paper,the main focus is on different risk management model and the importance of automated tools in risk managementt. With the automated risk management tool, the prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and rank the risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

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What this paper is about

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In this paper,the main focus is on different risk management model and the importance of automated tools in risk managementt. With the automated risk management tool, the prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and rank the risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In this paper,the main focus is on different risk management model and the importance of automated tools in risk managementt. With the automated risk management tool, the prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and rank the risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

Key concepts: Risk management, Project risk management, Computer science, Risk analysis (engineering), Risk management plan, Software, Ranking (information retrieval), Identification (biology)

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