Folksonomy-based term extraction for word cloud generation

  • Authors:
  • David Carmel;Erel Uziel;Ido Guy;Yosi Mass;Haggai Roitman

  • Affiliations:
  • IBM Research, Haifa lab, Haifa, Israel;IBM Research, Haifa lab, Haifa, Israel;IBM Research, Haifa lab, Haifa, Israel;IBM Research, Haifa lab, Haifa, Israel;IBM Research, Haifa lab, Haifa, Israel

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this work we study the task of term extraction for word cloud generation. We present a folksonomy-based term extraction method, called tag-boost, which boosts terms that are frequently used by the public to tag content. Our experiments with tag-boost-based term extraction over different domains demonstrate tremendous improvement in word cloud quality, as reflected by the agreement between extracted terms and manually assigned tags of the testing items. Additionally, we show that tag-boost can be effectively applied even in non-tagged domains, by using an external rich folksonomy borrowed from a well-tagged domain.