Probabilistic Graphical Framework for Predicting Software Project Risk
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ahn, Gilseung | - |
dc.contributor.author | Kwon, Minsung | - |
dc.contributor.author | Kang, Changwook | - |
dc.contributor.author | Hur, Sun | - |
dc.date.accessioned | 2021-06-22T12:03:22Z | - |
dc.date.available | 2021-06-22T12:03:22Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2018-03 | - |
dc.identifier.issn | 1598-7248 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/6426 | - |
dc.description.abstract | Project risk management is currently one of the main topics of interest for researchers and practitioners working in the area of project management. Risk management has been designated as one of the ten subject areas of the Project Management Body of Knowledge by the Project Management Institute. Since project risk management is closely associated with other project management areas, it is important to manage project risk in detail. In this paper, we suggest a method to predict software project risk by means of probabilistic graphical model. Concretely, we identify software development process referring to ISO/IEC 12207, an international standard for software lifecycle processes and construct a probabilistic model to predict risks. The framework we suggest not only forecasts the risks, but also finds critical factors to analyze project risk. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | KOREAN INST INDUSTRIAL ENGINEERS | - |
dc.title | Probabilistic Graphical Framework for Predicting Software Project Risk | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Hur, Sun | - |
dc.identifier.doi | 10.7232/iems.2018.17.1.120 | - |
dc.identifier.scopusid | 2-s2.0-85045142040 | - |
dc.identifier.wosid | 000429562600011 | - |
dc.identifier.bibliographicCitation | INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, v.17, no.1, pp.120 - 127 | - |
dc.relation.isPartOf | INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS | - |
dc.citation.title | INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS | - |
dc.citation.volume | 17 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 120 | - |
dc.citation.endPage | 127 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002326978 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.subject.keywordPlus | NEURAL-NETWORKS | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | DELPHI | - |
dc.subject.keywordAuthor | Project Management | - |
dc.subject.keywordAuthor | Project Risk Management | - |
dc.subject.keywordAuthor | Software Project Management | - |
dc.subject.keywordAuthor | Conditional Random Field | - |
dc.subject.keywordAuthor | Risk Prediction | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07406979 | - |
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