Recommendations based on different aspects of influences in social media

Chin Hui Lai, Duen-Ren Liu, Mei Lan Liu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Among the applications of Web 2.0, social networking sites continue to proliferate and the volume of content keeps growing; as a result, information overload causes difficulty for users attempting to choose useful and relevant information. In this work, we propose a novel recommendation method based on different types of influences: social, interest and popularity, using personal tendencies in regard to these three decision factors to recommend photos in a photo-sharing website, Flickr. Because these influences have different degrees of impact on each user, the personal tendencies related to these three influences are regarded as personalized weights; combining influence scores enables predicting the scores of items. The experimental results show that our proposed methods can improve the quality of recommendations.

Original languageEnglish
Pages (from-to)194-201
Number of pages8
JournalLecture Notes in Business Information Processing
Volume152
DOIs
StatePublished - 1 Jan 2013

Keywords

  • Collaborative filtering
  • Recommender system
  • Social influence
  • Social media
  • Social network
  • Web 2.0

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