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FairGRecs: Fair Group Recommendations by Exploiting Personal Health Information

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Book cover Database and Expert Systems Applications (DEXA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11030))

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Abstract

FairGRecs aims to offer valuable information to users, in the form of suggestions, via their caregivers, and improve as such the opportunities that users have to inform themselves online about health problems and possible treatments. Specifically, FairGRecs introduces a model for group recommendations, incorporating the notion of fairness. For computing similarities between users, we define a novel measure that is based on the semantic distance between users’ health problems. Our special focus is on providing valuable suggestions to a caregiver who is responsible for a group of users. We interpret valuable suggestions as ones that are both highly related and fair to the users of the group.

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Notes

  1. 1.

    http://www.icd10data.com/.

  2. 2.

    The work was partially supported by the EU project iManageCancer (H2020, #643529), and the TEKES Finnish project Virpa D project.

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Author information

Authors and Affiliations

  1. University of Tampere, Tampere, Finland

    Maria Stratigi & Kostas Stefanidis

  2. ICS-FORTH, Heraklion, Greece

    Haridimos Kondylakis

Authors
  1. Maria Stratigi
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  2. Haridimos Kondylakis
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  3. Kostas Stefanidis
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Corresponding author

Correspondence to Kostas Stefanidis .

Editor information

Editors and Affiliations

  1. Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sven Hartmann

  2. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

  3. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  4. University of Regensburg, Regensburg, Germany

    GĂĽnther Pernul

  5. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Stratigi, M., Kondylakis, H., Stefanidis, K. (2018). FairGRecs: Fair Group Recommendations by Exploiting Personal Health Information. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11030. Springer, Cham. https://doi.org/10.1007/978-3-319-98812-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-98812-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98811-5

  • Online ISBN: 978-3-319-98812-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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