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Envisioning the Future of Personalization Through Personal Informatics: A User Study

Author

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  • Federica Cena

    (Computer Science Department, University of Torino, Italy)

  • Amon Rapp

    (Computer Science Department, University of Torino, Italy)

  • Silvia Likavec

    (Computer Science Department, University of Torino, Italy)

  • Alessandro Marcengo

    (TIM, Torino, Italy)

Abstract

In recent years, User Modeling (UM) scenery is changing. With the recent advancements in wearable and mobile technologies, the amount and type of data that can be gathered about users and employed to build User Models is rapidly expanding. UM can now be enriched with data regarding different aspects of people's daily lives and is likely to deliver novel personalized services. All these changes bring forth new research questions about the kinds of services which could be improved, which of them would be the most useful, the ways of conveying effectively new forms of recommendations, and how users would perceive them. In this paper the authors tried to find answers to some of these questions by exploiting a novel personalized system to conduct a qualitative user study, with the aim to understand users' needs and expectations w.r.t. personalization enabled by the presence of wearable and mobile technologies.

Suggested Citation

  • Federica Cena & Amon Rapp & Silvia Likavec & Alessandro Marcengo, 2018. "Envisioning the Future of Personalization Through Personal Informatics: A User Study," International Journal of Mobile Human Computer Interaction (IJMHCI), IGI Global, vol. 10(1), pages 52-66, January.
    • Handle: RePEc:igg:jmhci0:v:10:y:2018:i:1:p:52-66
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    Cited by:

    1. Luz Santamaria-Granados & Juan Francisco Mendoza-Moreno & Gustavo Ramirez-Gonzalez, 2020. "Tourist Recommender Systems Based on Emotion Recognition—A Scientometric Review," Future Internet, MDPI, vol. 13(1), pages 1-38, December.

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