Preserving Privacy in Supply Chain Management: A Challenge for Next Generation Data Mining

dc.contributor.authorAhluwalia, Madhu V.
dc.contributor.authorChen, Zhiyuan
dc.contributor.authorGangopadhyay, Arrya
dc.contributor.authorGUO, Zhiling
dc.date.accessioned2025-06-05T14:02:49Z
dc.date.available2025-06-05T14:02:49Z
dc.date.issued2007-10-01
dc.descriptionProceedings of National Science Foundation Symposium on Next Generation Data Mining and Cyber-Enabled Discovery for Innovation NGDM 2007
dc.description.abstractIn this paper we identify a major area of research as a topic for next generation data mining. The research effort in the last decade on privacy preserving data mining has resulted in the development of numerous algorithms. However, most of the existing research has not been applied in any particular application context. Hence it is unclear whether the current algorithms are directly applicable in any particular problem context. In this paper we identify a significant application context that not only requires protection of privacy but also sophisticated data analysis. The area in question is supply chain management, arguably one of the most important research areas in production and operations management that has enormous practical relevance. We examine the area of supply chain management and identify research challenges and opportunities for privacy preserving data mining in the next generation.
dc.description.sponsorshipResearch supported in part by NSF grant IIS-IPS 0713345 to Zhiyuan Chen and Aryya Gangopadhyay
dc.description.urihttps://ink.library.smu.edu.sg/sis_research/1870
dc.format.extent6 pages
dc.genreconference papers and proceedings
dc.identifierdoi:10.13016/m2asrs-iyjb
dc.identifier.citationAhluwalia, Madhu, Zhiyuan CHEN, Arrya Gangopadhyay, and Zhiling GUO. “Preserving Privacy in Supply Chain Management: A Challenge for Next Generation Data Mining.” Proceedings of National Science Foundation Symposium on Next Generation Data Mining and Cyber-Enabled Discovery for Innovation NGDM 2007, October 1, 2007, 1–5. https://ink.library.smu.edu.sg/sis_research/1870
dc.identifier.urihttp://hdl.handle.net/11603/38603
dc.language.isoen_US
dc.publisherSingapore Management University
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC College of Engineering and Information Technology Dean's Office
dc.relation.ispartofUMBC Information Systems Department
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Information Systems Department
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International CC BY-NC-ND 4.0 Deed
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
dc.subjectUMBC Mobile, Pervasive and Sensor Computing Lab (MPSC Lab)
dc.subjectUMBC Cybersecurity Institute
dc.subjectUMBC Accelerated Cognitive Cybersecurity Laboratory
dc.titlePreserving Privacy in Supply Chain Management: A Challenge for Next Generation Data Mining
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-6984-7248

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