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Identifier 000413379
Title Fairness in group recommendations in the health domain
Alternative Title Δικαιοσύνη στις συστάσεις σε ομάδες στον τομέα της υγείας
Author Στρατήγη, Μαρία Σ.
Thesis advisor Πλεξουσάκης, Δημήτρης
Abstract During the last decade, the number of users who look for health-related information has impressively increased. On the other hand, health professionals have less and less time to recommend useful sources of such information online to their patients. To this direction, we target at streamlining the process of providing useful online information to patients by their caregivers and improving as such the opportunities that patients have to inform themselves online about diseases and possible treatments. Using our system, relevant and high quality information is delivered to patients based on their profile, as represented in their personal healthcare record data, facilitating an easy interaction by minimizing the necessary manual effort. Specifically, in this work, we propose a model for group recommendations incorporating fairness, following the collaborative filtering approach. As in collaborative filtering, it is crucial to identify the correct set of similar users, in addition to traditional methods, we pay particular attention on how to exploit user's health information. To this direction, we define a novel similarity 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. As such, we introduce in addition, a new aggregation method incorporating fairness and we compare it with current state of the art. Our experiments demonstrate the advantages of both the semantic similarity method and the fair aggregation design. To the best of our knowledge, this is the first work that introduces the concept of group recommendations incorporating fairness in the health domain.
Language English
Subject Personal health profile
Προσωπικές πληροφορίες υγείας
Issue date 2017-11-24
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/8/b/8/metadata-dlib-1513686176-940585-4996.tkl Bookmark and Share
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