Authors:
Abir Gorrab
;
Wala Rebhi
;
Narjes Bellamine Ben Saoud
and
Henda Ben Ghezala
Affiliation:
RIADI Laboratory, National School of Computer Sciences, University of Manouba, 2010, Tunisia
Keyword(s):
Recommendation Systems, Multidimensional Model, Generic User Profile, Complex Social Network, Context, Topic Recommendations.
Abstract:
Recommendation systems play a crucial role in providing relevant information through data analysis. One of the pivotal challenges in the recommendation process is modeling user profiles. However, many existing models focus on a single aspect to describe users, overlooking other valuable data. In response to this lim-itation, this paper introduces a comprehensive multidimensional model that captures various dimensions of a user within their complex social network. This model encompasses demographic, social, behavioral and homophilic dimensions, with the goal of offering more holistic recommendations tailored to different contexts. Towards the end of this article, we introduce a focused application of the multidimensional model. This specific application revolves around providing hashtag recommendations within the X platform (Twitter platform). This serves as a tangible demonstration of how the proposed model can be applied in a practical context within a real social network. The main
goal is to comprehensively assess the model’s efficacy in generating recommendations by utilizing a varied set of user-related information. To accomplish this, we introduce and evaluate a recommendation approach driven by our proposed user profile model, showcasing relevant and notable results.
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