A privacy-aware feature selection method for solving the personalization–privacy paradox in mobile wellness healthcare services. Issue 5 (1st April 2015)

• Record Type: Journal Article
• Authors: Lee, Namyeon; Kwon, Ohbyung
• Is Part Of: Expert systems with applications. Volume 42:Issue 5(2015)
• Page Start: 2764
• Page End: 2771
• Publication Date: 2015-04-01
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.11.031
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st080">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0200">The essence of personalization in mobile wellness healthcare (MWH) services is feature selection.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0205">A novel method of privacy-aware feature selection for individualized MWH is presented.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0210">An optimal set of features is automatically found to solve the personalization–privacy paradox.</p> </list-item> <list-item id="o0020"> <label></label> <p id="p0215">The results successfully show that the proposed method outperforms conventional methods.</p> </list-item> </list> </p> </sec> </abstract>