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Erschienen in:
Preface: Humans in Digital Marketplaces Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

26. Privacy Preserving Personalization in Complex Ecosystems

verfasst von : Anders Andersen, Randi Karlsen

Erschienen in: Digital Marketplaces Unleashed

Verlag: Springer Berlin Heidelberg

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Abstract

Personalization can be used to improve the quality of a service for a user. From the providers’ perspective personalization can be used to better target its users. Personalization is achieved by creating and maintaining a user profile that describes the user, her interest and her current context. A major concern with creating, maintaining and using user profiles is user privacy and trust. In this chapter we will discuss the process of creating and maintaining user profiles with a privacy preserving focus.

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Vorheriges Kapitel From Digital Retail to Real-Time Retail
Nächstes Kapitel Cognitive Computing – the new Paradigm of the Digital World
Literatur
1.
M. Gao, K. Liu and Z. Wu, “Personalisation in web computing and informatics: Theories, techniques, applications, and future research,” Information Systems Frontiers, vol. 12, no. 5, pp. 607–629, 2010.CrossRef
2.
M. Wiesner and D. Pfeifer, “Health recommender systems: concepts, requirements, technical basics and challenges,” International journal of environmental research and public health, vol. 11, no. 3, pp. 2580–2607, 2014.CrossRef
3.
B. Krulwich, “Lifestyle finder: Intelligent user profiling using large-scale demographic data,” AI magazine, vol. 18, no. 2, p. 37, 1997.
4.
S.-H. Min and I. Han, “Detection of the customer time-variant pattern for improving recommender systems,” Expert Systems with Applications, vol. 28, no. 2, pp. 189–199, 2005.CrossRef
5.
A. S. Das, M. Datar, A. Garg and S. Rajaram, “Google news personalization: scalable online collaborative filtering,” in Proceedings of the 16th international conference on World Wide Web, Banff, AB, Canada, 2007.CrossRef
6.
I. Guy, N. Zwerdling, I. Ronen, D. Carmel and E. Uziel, “Social media recommendation based on people and tags,” in Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, Geneva, Switzerland, 2010.CrossRef
7.
R. W. White, P. Bailey and L. Chen, “Predicting user interests from contextual information,” in Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, Boston, MA, USA, 2009.CrossRef
8.
R. W. White and J. Huang, “Assessing the scenic route: measuring the value of search trails in web logs,” in Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, Geneva, Switzerland, 2010.CrossRef
9.
M. Harvey, F. Crestani and M. J. Carman, “Building user profiles from topic models for personalised search,” in Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, San Francisco, CA, USA, 2013.CrossRef
10.
P. N. Bennett, R. W. White, W. Chu, S. T. Dumais, P. Bailey, F. Borisyuk and X. Cui, “Modeling the Impact of Short- and Long-term Behavior on Search Personalization,” in Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Portland, Oregon, USA, 2012.CrossRef
11.
M. Balabanovic and Y. Shoham, “Fab: content-based, collaborative recommendation,” Communications of the ACM, vol. 40, no. 3, pp. 66–72, 1997.CrossRef
12.
M. Gao, K. Liu and Z. Wu, “Personalisation in web computing and informatics: Theories, techniques, applications, and future research,” Information Systems Frontiers, vol. 12, no. 5, pp. 607–629, 2010.CrossRef
13.
M. R. Ghorab, D. Zhou, A. O’Connor and V. Wade, “Personalised information retrieval: survey and classification,” User Modeling and User-Adapted Interaction, vol. 23, no. 4, pp. 381–443, 2013.CrossRef
14.
S. Gauch, M. Speretta, A. Chandramouli and A. Micarelli, “User profiles for personalized information access,” in The adaptive web, P. Brusilovsky, A. Kobsa and W. Nejdl, Eds., Berlin Heidelberg NewYork, Springer, 2007, pp. 54–89.CrossRef
15.
A. Andersen and R. Karlsen, “User profiling through NFC interactions: Mining NFC-based user information from mobile devices and back-end systems,” in Proceedings of the 14th International Symposium on Mobility Management and Wireless Access, Malta, 2016.CrossRef
16.
S. Panjwani, N. Shrivastava, S. Shukla and S. Jaiswal, “Understanding the privacy-personalization dilemma for web search: a user perspective,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, 2013.CrossRef
17.
M. Alaggan, S. Gambs and A.-M. Kermarrec, “Heterogeneous differential privacy,” arXiv preprint arXiv:1504.06998, 2015.
18.
A. Andersen, T. Hardersen and N. Schirmer, “Privacy for Cloud Storage,” in ISSE 2014 Securing Electronic Business Processes: Highlights of the Information Security Solutions Europe 2014 Conference, Springer, 2014.
19.
E. Toch, Y. Wang and L. F. Cranor, “Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems,” User Modeling and User-Adapted Interaction, vol. 22, no. 1–2, pp. 203–220, 2012.CrossRef
20.
A. Friedman, B. P. Knijnenburg, K. Vanhecke, L. Martens and S. Berkovsky, “Privacy aspects of recommender systems,” in Recommender Systems Handbook, Springer, 2015, pp. 649–688.CrossRef
21.
L. Cassel and U. Wolz, “Client Side Personalization,” in Proceedings of the joint DELOS-NSF workshop on personalization and recommender systems in digital libraries, Dublin, 2001.
22.
M. Asif and J. Krogstie, “Mobile client-side personalization,” in Proceedings of the 2013 International Conference on Privacy and Security in Mobile Systems (PRISMS), 2013.CrossRef
23.
A. Munch-Ellingsen, A. Andersen, S. Akselsen and R. Karlsen, “Customer managed security domain on mobile network operators’ SIM cards: Opportunities to enable new business models,” in Marktplätze im Umbruch: Digitale Strategien und das Zusammenwachsen von Shop, Online-Business sowie Services im Mobilen Internet, Springer, 2015.
24.
C. Dwork, “Differential privacy: A survey of results,” in Proceedings of the International Conference on Theory and Applications of Models of Computation, 2008.MATH
25.
A. Andersen, K. Y. Yigzaw and R. Karlsen, “Privacy preserving health data processing,” in Proceedings of the 16th International Conference on e-Health Networking, Applications and Services (Healthcom), 2014.CrossRef
26.
C. Gentry, A fully homomorphic encryption scheme, Stanford University, 2009.MATH
27.
M. K. L. Z. W. Gao, “Personalisation in web computing and informatics: Theories, techniques, applications, and future research,” Information Systems Frontiers, vol. 12, no. 5, pp. 607–629, 2010.CrossRef
Metadaten
Titel
Privacy Preserving Personalization in Complex Ecosystems
verfasst von
Anders Andersen
Randi Karlsen
Copyright-Jahr
2018
Verlag
Springer Berlin Heidelberg
Buch
Digital Marketplaces Unleashed

Print ISBN: 978-3-662-49274-1

Electronic ISBN: 978-3-662-49275-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-662-49275-8_26

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