OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

LoTrust: A social Trust Level model based on time-aware social interactions and interests similarity

Kalaï, Ahlem and Abdelghani, Wafa and Zayani, Corinne Amel and Amous, Ikram LoTrust: A social Trust Level model based on time-aware social interactions and interests similarity. (2016) In: PST 2016 : 14th International Conference on Privacy, Security and Trust, 12 December 2016 - 14 December 2016 (Auckland, New Zealand).

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
418kB

Official URL: http://dx.doi.org/10.1109/PST.2016.7906967

Abstract

With the immense growth of online social applications, trust plays a more and more important role in connecting users to each other, sharing their personal information and attracting him to receive recommendations. Therefore, how to obtain trust relationships through mining online social networks became a critical issue. To calculate the level of trust between two users, many computational trust models are proposed which mainly rely on the social network structure, the explicit trust from user to another, the users' behaviors, or the users' similarity, etc. However, the majority of these models ignored the temporal factor. In this paper, we propose a trust relationship detection mechanism from an egocentric social network in order to compute the trust level between an active user and his directed friends. We propose a Level of social Trust model, that we called LoTrust, which is suitable for personalized recommendation purpose. This computational model founded on novel trust metric which is based not only on the users' interests similarity according to their semantic social profiles (RDF/FOAF), but also takes into account the time factor of the users' active interactions (e.g comments, share photo, wall posts, messages). We perform experiments on real life dataset extracted from Facebook. The experimental results demonstrated how our LoTrust model produces satisfactory results than other computational models.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The original PDF of the article can be found at http://ieeexplore.ieee.org/document/7906967/ Thanks to PST 2016 : 14th International Conference on Privacy, Security and Trust : http://pst2016.unitec.ac.nz/
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > Université de Sfax (TUNISIA)
Laboratory name:
Statistics:download
Deposited By: Abdelghani Wafa
Deposited On:13 Dec 2017 07:37

Repository Staff Only: item control page