Christos K. Georgiadis
Privacy-preserving recommendations in context-aware mobile environments
Georgiadis, Christos K.; Stiakakis, Emmanouil; Polatidis, Nikolaos; Pimenidis, Elias
Authors
Emmanouil Stiakakis
Nikolaos Polatidis
Dr Elias Pimenidis Elias.Pimenidis@uwe.ac.uk
Senior Lecturer in Computer Science
Abstract
© Emerald Publishing Limited. Purpose - This paper aims to address privacy concerns that arise from the use of mobile recommender systems when processing contextual information relating to the user. Mobile recommender systems aim to solve the information overload problem by recommending products or services to users of Web services on mobile devices, such as smartphones or tablets, at any given point in time and in any possible location. They use recommendation methods, such as collaborative filtering or content-based filtering and use aconsiderable amount of contextual information to provide relevant recommendations. However, because of privacy concerns, users are not willing to provide the required personal information that would allow their views to be recorded and make these systems usable. Design/methodology/approach - This work is focused on user privacy by providing a method for context privacy-preservation and privacy protection at user interface level. Thus, a set of algorithms that are part of the method has been designed with privacy protectionin mind, which isdone byusing realistic dummy parameter creation. Todemonstrate the applicability of the method, arelevant context-aware data set has been used to run performance and usability tests. Findings - The proposed method has been experimentally evaluated using performance and usability evaluation tests and is shown that with a small decrease in terms of performance, user privacy can be protected. Originality/value - This is a novel research paper that proposed a method for protecting the privacy of mobile recommender systems users when context parameters are used.
Citation
Stiakakis, E., Georgiadis, C. K., Polatidis, N., & Pimenidis, E. (2017). Privacy-preserving recommendations in context-aware mobile environments. Information and Computer Security, 25(1), 62-79. https://doi.org/10.1108/ICS-04-2016-0028
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 7, 2016 |
Publication Date | Jan 1, 2017 |
Deposit Date | Jun 22, 2016 |
Publicly Available Date | Mar 29, 2024 |
Journal | Information and Computer Security |
Print ISSN | 2056-4961 |
Electronic ISSN | 2056-4961 |
Publisher | Emerald |
Peer Reviewed | Peer Reviewed |
Volume | 25 |
Issue | 1 |
Pages | 62-79 |
DOI | https://doi.org/10.1108/ICS-04-2016-0028 |
Keywords | mobile recommender systems, context-awareness, privacy, dummy-based, user interface |
Public URL | https://uwe-repository.worktribe.com/output/897525 |
Publisher URL | http://dx.doi.org/10.1108/ICS-04-2016-0028 |
Files
journal_ics_v10_EP_NP_CG_ES_Final version.pdf
(551 Kb)
PDF
You might also like
Fast and accurate evaluation of collaborative filtering recommendation algorithms
(2022)
Conference Proceeding
Problem classification for tailored help desk auto replies
(2022)
Conference Proceeding
Supporting patient nutrition in critical care units
(2022)
Conference Proceeding
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search