Measuring Similarity of Interests for Clustering Taggers and Resources

Measuring Similarity of Interests for Clustering Taggers and Resources

Christo Dichev, Jinsheng Xu, Darina Dicheva, Jinghua Zhang
Copyright: © 2009 |Pages: 20
DOI: 10.4018/jvcsn.2009070101
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Collaborative tagging systems demonstrate the potential to generate collectively built organization structures forming the basis for social navigation and shared knowledge. The effectiveness of these systems for finding and re-finding information depends not only on the created tag structures but also on the ability to identify similar users. In this article, we present our study on measuring user similarity based on shared interests, utilizing data from del.icio.us. The authors propose several methods for measuring similarities aimed at clustering tags and users. They also report our initial results related to implicit grouping of tags and users.

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 10: 4 Issues (2018)
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing