Social view based user modeling for recommendation in tagging systems by association rules

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Social tagging systems such as Facebook, YouTube, del.icio.us, Flickr become popular recent years and have achieved widespread success. State-of-art user modeling approaches in tagging systems usually use a vector of weighted tags. Unfortunately, typical user modeling methods using a vector of weighted tags which are based on personal view only and ignore the social view, have some inherent drawbacks. As in a social network like collaborative tagging system, it is subjective and incomplete to profile using only personal view. In this paper, a novel approach applying association rules is proposed to extend user profiles from the social view. The enriched user profile is a harvest from both personal view and social view. Algorithms of personalized recommendations for tags and items are presented. Also experimental results of using the profile we proposed are discussed.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010
DOIs
StatePublished - 2010
Event2nd International Workshop on Intelligent Systems and Applications, ISA2010 - Wuhan, China
Duration: 22 May 201023 May 2010

Publication series

NameProceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010

Conference

Conference2nd International Workshop on Intelligent Systems and Applications, ISA2010
Country/TerritoryChina
CityWuhan
Period22/05/1023/05/10

Keywords

  • Association rule
  • Model
  • Recommendation system
  • Social view
  • Tagging system

Fingerprint

Dive into the research topics of 'Social view based user modeling for recommendation in tagging systems by association rules'. Together they form a unique fingerprint.

Cite this