Methodologies for Improved Tag Cloud Generation with Clustering

Martin Leginus, Peter Dolog, Ricardo Gomes Lage, Frederico Durao

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

6 Citations (Scopus)


Tag clouds are useful means for navigation in the social web
systems. Usually the systems implement the tag cloud generation based
on tag popularity which is not always the best method. In this paper
we propose methodologies on how to combine clustering into the tag
cloud generation to improve coverage and overlap. We study several clustering algorithms to generate tag clouds. We show that by extending
cloud generation based on tag popularity with clustering we slightly improve coverage. We also show that if the cloud is generated by clustering
independently of the tag popularity baseline we minimize overlap and
increase coverage. In the first case we therefore provide more items for a
user to explore. In the second case we provide more diverse items for a
user to explore. We experiment with the methodologies on two different
datasets: Delicious and Bibsonomy. The methodologies perform slightly
better on bibsonomy due to its specific focus. The best performing is the
hierarchical clustering.
Original languageEnglish
Title of host publicationProceedings of the 12th international conference on Web Engineering
Number of pages15
Publication date2012
Publication statusPublished - 2012
EventInternational conference on Web Engineering - Berlin, Germany
Duration: 23 Jul 201227 Jul 2012
Conference number: 12


ConferenceInternational conference on Web Engineering
SeriesLecture Notes in Computer Science


  • tag clouds
  • clustering


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