Followee recommendation in microblog using matrix factorization model with structural regularization

Yan Yu, Robin G. Qiu

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.

Original languageEnglish (US)
Article number420841
JournalThe Scientific World Journal
Volume2014
DOIs
StatePublished - 2014

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All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)

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