Title: Personalised recommendation algorithm for social network based on two-dimensional correlation

Authors: Aimei Zhu

Addresses: School of software, Hunan Vocational College of Science and Technology, Changsha City of Hunan Province, 410004, China

Abstract: In order to recommend friends in a real sense based on the personalised needs of users. A personalised recommendation algorithm based on two-dimensional correlation (FRBOT) was proposed for social network. In the proposed model, the interest similarity and trust relationship among users were combined with probability matrix decomposition to analyse the potential factor characteristics of the same preferences of selected trust users and target users. Compared with general matrix decomposition algorithm and personalised recommendation method based on user trust, the algorithm has evident advantages and can improve user satisfaction. The experimental results show that the performance of the proposed friend recommendation method is significantly improved compared with that of the existing friend recommendation methods.

Keywords: friend recommendation; social network; latent semantic model; random walk.

DOI: 10.1504/IJAACS.2020.109807

International Journal of Autonomous and Adaptive Communications Systems, 2020 Vol.13 No.2, pp.195 - 209

Received: 29 Sep 2019
Accepted: 05 Mar 2020

Published online: 24 Sep 2020 *

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