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Privacy and Personalization. The Trade-off between Data Disclosure and Personalization Benefit

: Wadle, Lisa-Marie; Martin, Noemi; Ziegler, Daniel

Preprint urn:nbn:de:0011-n-5522649 (985 KByte PDF)
MD5 Fingerprint: bf6b7b95763fa42fed19fa99b9483b19
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Created on: 23.7.2019

Papadopoulos, George Angelos (General Chair) ; Association for Computing Machinery -ACM-:
UMAP 2019 Adjunct, 27th Conference on User Modeling, Adaptation and Personalization. Adjunct Publication : Larnaca, Cyprus, June 09 - 12, 2019
New York: ACM, 2019
ISBN: 978-1-4503-6711-0
Conference on User Modeling, Adaptation and Personalization (UMAP) <27, 2019, Larnaca>
Conference Paper, Electronic Publication
Fraunhofer IAO ()
Fraunhofer IBP ()

Personalization in principle cannot happen without information about individuals, requiring personalization systems to comply with official privacy regulations. However, in order to design personalization systems that provide the best possible privacy-related user experience, a more human-centered perspective has to be taken into account. As a first step towards this goal, in the present work we show the setup and results of an online survey investigating the relation between the intention to disclose certain categories of personal data and the type of benefit promised by personalization.