Social Recommendations within the Multimedia Sharing Systems

TL;DR

This paper introduces a multirelational social network model for multimedia sharing systems that personalizes social recommendations by integrating social and semantic links, adapting suggestions to user preferences.

Contribution

It proposes a novel multirelational social network concept that combines social and object-based relationships for personalized recommendations.

Findings

The model effectively generates personalized social suggestions.

Experiments confirm the usefulness of the multirelational approach.

The system adapts recommendations based on user-specific weights.

Abstract

The social recommender system that supports the creation of new relations between users in the multimedia sharing system is presented in the paper. To generate suggestions the new concept of the multirelational social network was introduced. It covers both direct as well as object-based relationships that reflect social and semantic links between users. The main goal of the new method is to create the personalized suggestions that are continuously adapted to users' needs depending on the personal weights assigned to each layer from the social network. The conducted experiments confirmed the usefulness of the proposed model.