Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Maximizing user trust and item rating to overcome the problems using trust-based matrix factorization techniques

Author : Seelaboyina Charan Teja 1 M. Krishna Satya Varma 2

Date of Publication :7th December 2017

Abstract: Collaborative filtering inherently suffers from the data sparsity and cold start issues. Social networks are shown helpful to help alleviate these problems. However, social connections may not be available in several real systems, whereas implicit and explicit item relationships are lack of study. During this paper, we tend to propose TrustSVD, a trust-based matrix factorization model by taking into consideration implicit and explicit item relationships. Especially, we apply an adapted approach to reveal implicit and explicit item relationships in terms of item-to-item and group-to-item associations, which are then accustomed regularize the generation of low-rank user- and item-feature matrices. Experimental results on four real-world datasets demonstrate the superiority of our proposed approach against other counterparts.

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