DocumentCode :
3263490
Title :
Granular computing in privacy-preserving data mining
Author :
Zhan, Justin ; Lin, Tsau Young
Author_Institution :
Heinz Sch., Carnegie Mellon Univ., Pittsburgh, PA
fYear :
2008
fDate :
26-28 Aug. 2008
Firstpage :
86
Lastpage :
92
Abstract :
Granular computing is an emerging computing paradigm of information processing. It concerns the processing of complex information entities, called ldquoinformation granulesrdquo, which appear in the process of data abstraction and derivation of knowledge from information. The granular computing paradigm has been applied to many applications and we will address the application of granular computing in privacy-preserving data mining. We will use privacy-preserving association rule mining and privacy-preserving k-nearest neighbor classification to illustrate how the paradigm of granular computing has been applied.
Keywords :
data mining; data privacy; pattern classification; data abstraction; granular computing; information granules; information processing; privacy-preserving association rule mining; privacy-preserving data mining; privacy-preserving k-nearest neighbor classification; Association rules; Computer applications; Computer science; Data analysis; Data mining; Data privacy; Databases; Information processing; Insurance; Protection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-2512-9
Electronic_ISBN :
978-1-4244-2513-6
Type :
conf
DOI :
10.1109/GRC.2008.4664790
Filename :
4664790
Link To Document :
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