DI-UMONS : Dépôt institutionnel de l’université de Mons

Recherche transversale
(titres de publication, de périodique et noms de colloque inclus)
2017-09-18 - Colloque/Article dans les actes avec comité de lecture - Anglais - 12 page(s)

Rafailidis Dimitrios , Crestani Fabio, "Multiple Random Walks for Personalized Ranking with Trust and Distrust" in TPDL 2017, Thessaloniki, Greece, 2017

  • Codes CREF : Informatique générale (DI1162)
  • Unités de recherche UMONS : Systèmes d'information (S832)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut de Recherche sur les Systèmes Complexes (Complexys)
  • Centres UMONS : Modélisation mathématique et informatique (CREMMI)

Abstract(s) :

(Anglais) Social networks with trust and distrust relationships has been an emerging topic, aiming at identifying users' friends and foes when sharing information in social networks or purchasing products online. In this study we investigate how to generate accurate personalized rankings while considering both trust and distrust user relationships. This paper includes the following contributions, first we propose a social inference step of missing (indirect) trust relationships via multiple random walks, while considering users' direct trust and distrust relationships during the inference. In doing so, we can better capture the missing trust relationships between users in an enhanced signed network. Then, we introduce a regularization framework to account for (i) the structural properties of the enhanced graph with the inferred trust relationships, and (ii) the user's trust and distrust personalized preferences in the graph to produce his/her personalized ranking list. We evaluate the performance of the proposed approach on a benchmark dataset from Slashdot. Our experiments demonstrate the superiority of the proposed approach over state-of-the-art methods that also consider trust and distrust relationships in the personalized ranking task.