The University of Southampton
University of Southampton Institutional Repository

Multiple Interests of Users in Collaborative Tagging Systems

Yeung, CMA, Gibbins, N and Shadbolt, N (2009) Multiple Interests of Users in Collaborative Tagging Systems WEAVING SERVICES AND PEOPLE ON THE WORLD WIDE WEB, pp. 255-274.

Record type: Article


Performance of recommender systems depends on whether the user profiles contain accurate information about the interests of the users, and this ill turn relies on whether enough information about their interests can be collected. Collaborative tagging systems allow users to use their own words to describe their favourite resources, resulting in some user-generated categorisation schemes commonly known as folksonomies. Folksonomics thus contain rich information about the interests of the users, which can be used to support various recommender systems. Our analysis of the folksonomy in Delicious reveals that the interests of a single user can be very diverse. Traditional methods for representing interests of users are usually not able to reflect Such diversity. We propose a method to construct user profiles of multiple interests from folksonomies based oil a network clustering technique. Our evaluation shows that the proposed method is able to generate user profiles which reflect the diversity Of user interests and can be used as a basis of providing more focused recommendation to the users.

Full text not available from this repository.

More information

Published date: 2009
Additional Information: Imported from ISI Web of Science
Organisations: Web & Internet Science


Local EPrints ID: 270544
PURE UUID: 5288ff11-8b9e-4fec-9953-c5dc3134adc9

Catalogue record

Date deposited: 21 Apr 2010 07:46
Last modified: 18 Jul 2017 06:51

Export record


Author: CMA Yeung
Author: N Gibbins
Author: N Shadbolt

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.