Privacy in spatiotemporal data mining

dc.creator	Bonchi, F.	en
dc.creator	Saygin, Y.	en
dc.creator	Verykios, V. S.	en
dc.creator	Atzori, M.	en
dc.creator	Gkoulalas-Divanis, A.	en
dc.creator	Kaya, S. V.	en
dc.creator	Savaś, E.	en
dc.date.accessioned	2015-11-23T10:23:59Z
dc.date.available	2015-11-23T10:23:59Z
dc.date.issued	2008
dc.identifier	10.1007/978-3-540-75177-9_12
dc.identifier.isbn	9783540751762
dc.identifier.uri	http://hdl.handle.net/11615/26347
dc.description.abstract	Privacy is an essential requirement for the provision of electronic and knowledgebased services in modern e-business, e-commerce, e-government, and e-health environments. Nowadays, service providers can easily track individuals' actions, behaviors, and habits. Given large data collections of person-specific information, providers can mine data to learn patterns, models, and trends that can be used to provide personalized services. The potential benefits of data mining are substantial, but it is evident that the collection and analysis of sensitive personal data arouses concerns about citizens' privacy, confidentiality, and freedom. © Springer Berlin Heidelberg 2008.	en
dc.source	Mobility, Data Mining and Privacy: Geographic Knowledge Discovery	en
dc.source.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-67650258951&partnerID=40&md5=d3c99786e3617d0aa3252b18c8c5e62a
dc.title	Privacy in spatiotemporal data mining	en
dc.type	bookChapter	en

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