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00000nam a22000005i 4500 |
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978-3-642-30487-3 |
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120811s2013 gw | s |||| 0|eng d |
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|a 9783642304873
|9 978-3-642-30487-3
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|a 10.1007/978-3-642-30487-3
|2 doi
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|a Discrimination and Privacy in the Information Society
|h [electronic resource] :
|b Data Mining and Profiling in Large Databases /
|c edited by Bart Custers, Toon Calders, Bart Schermer, Tal Zarsky.
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250 |
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|a 1st ed. 2013.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XVIII, 370 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Studies in Applied Philosophy, Epistemology and Rational Ethics,
|x 2192-6263 ;
|v 3
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|a Part I Opportunities of Data Mining and Profiling -- Part II Possible Discrimination and Privacy Issues -- Part III Practical Applications -- Part IV Solutions in Code -- Part V Solutions in Law, Norms and the Market.
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|a Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth. .
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|a Computational intelligence.
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650 |
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|a Ethics.
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650 |
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|a Data mining.
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650 |
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|a Database management.
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|a Criminal law.
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|a Computational Intelligence.
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650 |
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|a Moral Philosophy and Applied Ethics.
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650 |
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|a Data Mining and Knowledge Discovery.
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650 |
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|a Database Management.
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650 |
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|a Criminal Law and Criminal Procedure Law.
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700 |
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|a Custers, Bart.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Calders, Toon.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Schermer, Bart.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Zarsky, Tal.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
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|t Springer Nature eBook
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776 |
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|i Printed edition:
|z 9783642304880
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776 |
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|i Printed edition:
|z 9783642441134
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776 |
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8 |
|i Printed edition:
|z 9783642304866
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830 |
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|a Studies in Applied Philosophy, Epistemology and Rational Ethics,
|x 2192-6263 ;
|v 3
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856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/978-3-642-30487-3
|z Texto Completo
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912 |
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|a ZDB-2-ENG
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912 |
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|a ZDB-2-SXE
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950 |
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|a Engineering (SpringerNature-11647)
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950 |
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|a Engineering (R0) (SpringerNature-43712)
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