By Topic

Integrating Social Relations into Personalized Tag Recommendation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kaipeng Liu ; Harbin Inst. of Technol., Harbin, China ; Binxing Fang

Personalized tag recommendation is to provide a user with a ranked list of tags for a specific resource that best serves the user's needs. In this paper, we proposed a personalized tag recommendation algorithm incorporating with users' social relations. We model the social annotations made by the collaborative users and the social relations between them with a graph model. We associate each node in this graph with a tag preference vector, which is then refined through a random walk procedure over this graph. The tag preferences of the active user and resource are finally combined to generate the recommended tags. We conduct experiments on the Delicious. Experimental results demonstrate the effectiveness of the proposed algorithm.

Published in:

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2010 2nd International Conference on  (Volume:1 )

Date of Conference:

26-28 Aug. 2010