Can social tags help you find what you want?

Khasfariyati Razikin*, Dion Hoe Lian Goh, Alton Y.K. Chua, Chei Sian Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

One of the uses of social tagging is to associate freely selected terms (tags) to resources for sharing resources among tag consumers. This enables tag consumers to locate new resources through the collective intelligence of other tag creators, and offers a new avenue for resource discovery. This paper investigates the effectiveness of tags as resource descriptors determined through the use of text categorisation using Support Vector Machines. Two text categorisation experiments were done for this research, and tags and web pages from del.icio.us were used. The first study concentrated on the use of terms as its features. The second study used both terms and its tags as part of its feature set. The results indicate that the tags were not always reliable indicators of the resource contents. At the same time, the results from the terms only experiment were better compared to the experiment with terms and tags. A deeper analysis of a sample of tags and documents were also conducted and implications of this research are discussed.

Original languageEnglish
Title of host publicationResearch and Advanced Technology for Digital Libraries - 12th European Conference, ECDL 2008, Proceedings
Pages50-61
Number of pages12
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event12th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2008 - Aarhus, Denmark
Duration: Sept 14 2008Sept 19 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5173 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2008
Country/TerritoryDenmark
CityAarhus
Period9/14/089/19/08

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Resource descriptors
  • Resource discovery
  • Social tagging
  • Support vector machines

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