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dc.contributor.authorCorinna, Rutschi-
dc.contributor.authorNicholas, Berente-
dc.contributor.authorFrederick, Nwanganga-
dc.date.accessioned2023-04-13T08:27:20Z-
dc.date.available2023-04-13T08:27:20Z-
dc.date.issued2023-
dc.identifier.govdochttps://link.springer.com/article/10.1007/s10796-023-10388-4-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7898-
dc.descriptionCC BYvi
dc.description.abstractData sensitivity and domain specificity challenges arise in reuse of machine learning applications. We identify four types of machine learning applications based on different reuse strategies: generic, distinctive, selective, and exclusive. We conclude with lessons for developing and deploying machine learning applications.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectData Sensitivityvi
dc.subjectDomain Specificityvi
dc.titleData Sensitivity and Domain Specificity in Reuse of Machine Learning Applicationsvi
dc.typeBookvi
Appears in CollectionsOER - Kinh tế và Quản lý

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