Graph based techniques for tag cloud generation.

Martin Leginus, Peter Dolog, Ricardo Gomes Lage

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

6 Citations (Scopus)


Tag cloud is one of the navigation aids for exploring documents. Tag cloud also link documents through the user defined terms. We explore various graph based techniques to improve the tag cloud generation. Moreover, we introduce relevance measures based on underlying data such as ratings or citation counts for improved measurement of relevance of tag clouds. We show, that on the given data sets, our approach outperforms the state of the art baseline methods with respect to such relevance by 41 % on Movielens dataset and by 11 % on Bibsonomy data set.
Original languageEnglish
Title of host publicationProceedings of the 24th ACM Conference on Hypertext and Social Media
Number of pages10
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery
Publication dateMay 2013
ISBN (Print)978-1-4503-1967-6
Publication statusPublished - May 2013
Event24th ACM Conference on Hypertext and Social Media - Paris, France
Duration: 1 May 20133 May 2013
Conference number: 24


Conference24th ACM Conference on Hypertext and Social Media


  • Tag cloud
  • Graph Theory


Dive into the research topics of 'Graph based techniques for tag cloud generation.'. Together they form a unique fingerprint.

Cite this