A Random Walk Based Model Incorporating Social Information for Recommendations

Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system. In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data sparsity and cold start problems in recommendation systems. More precisely, we construct a directed graph whose nodes consist of items and users, together with item content, user profile and social network information. We incorporate user's ratings into edge settings in the graph model. The model provides personalized recommendations and predictions to individuals and groups. The proposed algorithms are evaluated on MovieLens and Epinions datasets. Experimental results show that the proposed methods perform well compared with other graph-based methods, especially in the cold start case.

Original languageEnglish (US)
Title of host publication2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012
PublisherIEEE Computer Society
ISBN (Print)9781467310260
DOIs
StatePublished - Jan 1 2012
Event2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 - Santander, Spain
Duration: Sep 23 2012Sep 26 2012

Publication series

NameIEEE International Workshop on Machine Learning for Signal Processing, MLSP
ISSN (Print)2161-0363
ISSN (Electronic)2161-0371

Other

Other2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012
CountrySpain
CitySantander
Period9/23/129/26/12

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Signal Processing

Keywords

  • Recommendation system
  • hybrid collaborative filtering model
  • random walk
  • social networks

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  • Cite this

    Shang, S., Kulkarni, S. R., Cuff, P. W., & Hui, P. (2012). A Random Walk Based Model Incorporating Social Information for Recommendations. In 2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012 [6349732] (IEEE International Workshop on Machine Learning for Signal Processing, MLSP). IEEE Computer Society. https://doi.org/10.1109/MLSP.2012.6349732