A Design of Fuzzy Rule-Based Models With Data Privacy

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dc.contributor.authorPedrycz, Witold
dc.date.accessioned2024-05-19T14:40:13Z
dc.date.available2024-05-19T14:40:13Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractOne of the currently visible requirements of data analysis concerns data privacy. The quest for privacy triggers design challenges in the construction of machine learning models. In this study, we propose a novel and systematic design methodology of fuzzy design rule-based models completed in the following privacy-driven environment. Multidimensional data are available for model design in two different formats: those attributes that are privacy sensitive are provided at the higher nonnumeric level of abstraction represented in the form of information granules, while the remaining ones are available directly. It is shown that the granular manifestation of data becomes beneficial in the formation of the conditions of the rules, whereas numeric attributes are available for the construction of the conclusions of the rules. The generic development scheme is discussed. Some generalization is introduced to cope with a number of data islands associated with the corresponding data owners. It is shown that the formation of the data structure calls for a mechanism of collaborative clustering. A way of handling information granules at different levels of information granularity is discussed. Some illustrative examples are presented.en_US
dc.identifier.doi10.1109/TFUZZ.2022.3229525
dc.identifier.endpage2890en_US
dc.identifier.issn1063-6706
dc.identifier.issn1941-0034
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85144795433en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2885en_US
dc.identifier.urihttps://doi.org10.1109/TFUZZ.2022.3229525
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4926
dc.identifier.volume31en_US
dc.identifier.wosWOS:001043156400032en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Fuzzy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectCollaborationen_US
dc.subjectData Privacyen_US
dc.subjectFuzzy Clusteringen_US
dc.subjectInformation Granularityen_US
dc.subjectPrivacy-Sensitive Attributesen_US
dc.subjectRule-Based Modelen_US
dc.titleA Design of Fuzzy Rule-Based Models With Data Privacyen_US
dc.typeArticleen_US

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