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Social-Based Collaborative Recommendation: Bees Swarm Optimization Based Clustering Approach

  • Lamia BerkaniEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11815)

Abstract

This paper focuses on the recommendation of items in social networks, through which the social information is formalized and combined with the collaborative filtering algorithm using an optimized clustering method. In this approach, users are clustered from the views of both user similarity and trust relationships. A Bees Swarm optimization algorithm is designed to optimize the clustering process and therefore recommend the most appropriate items to a given user. Extensive experiments have been conducted, using the well-known Epinions dataset, to demonstrate the effectiveness of the proposed approach compared to the traditional recommendation algorithms.

Keywords

Social recommendation Collaborative filtering Clustering Optimization Bees Swarm Optimization algorithm BSO 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Laboratory for Research in Artificial Intelligence (LRIA), Department of Computer ScienceUSTHB UniversityBab Ezzouar, AlgiersAlgeria

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