Experimental Comparison of Semantic Word Clouds

  • Lukas Barth
  • Stephen G. Kobourov
  • Sergey Pupyrev
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8504)


We study the problem of computing semantics-preserving word clouds in which semantically related words are close to each other. We implement three earlier algorithms for creating word clouds and three new ones. We define several metrics for quantitative evaluation of the resulting layouts. Then the algorithms are compared according to these metrics, using two data sets of documents from Wikipedia and research papers. We show that two of our new algorithms outperform all the others by placing many more pairs of related words so that their bounding boxes are adjacent. Moreover, this improvement is not achieved at the expense of significantly worsened measurements for the other metrics.


Edge Weight Semantic Relation Ranking Function Term Frequency Related Word 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Barth, L., et al.: Semantic word cloud representations: Hardness and approximation algorithms. In: Pardo, A., Viola, A. (eds.) LATIN 2014. LNCS, vol. 8392, pp. 514–525. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  2. 2.
    Cui, W., Wu, Y., Liu, S., Wei, F., Zhou, M., Qu, H.: Context-preserving dynamic word cloud visualization. IEEE Comput. Graph. Appl. 30(6), 42–53 (2010)CrossRefGoogle Scholar
  3. 3.
    Deutsch, S., Schrammel, J., Tscheligi, M.: Comparing different layouts of tag clouds: Findings on visual perception. In: Ebert, A., Dix, A., Gershon, N.D., Pohl, M. (eds.) HCIV (INTERACT) 2009. LNCS, vol. 6431, pp. 23–37. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  4. 4.
    Erkan, G., Radev, D.R.: LexRank: Graph-based lexical centrality as salience in text summarization. J. Artificial Intelligence Res. 22(1), 457–479 (2004)Google Scholar
  5. 5.
    Koh, K., Lee, B., Kim, B.H., Seo, J.: ManiWordle: Providing flexible control over Wordle. IEEE Trans. Vis. Comput. Graphics 16(6), 1190–1197 (2010)CrossRefGoogle Scholar
  6. 6.
    Lawler, E.L.: Fast approximation algorithms for knapsack problems. Math. Oper. Res. 4(4), 339–356 (1979)CrossRefzbMATHMathSciNetGoogle Scholar
  7. 7.
    Li, H., Abe, N.: Word clustering and disambiguation based on co-occurrence data. In: Int. Conf. Comput. Linguistics, vol. 2, pp. 749–755. Association for Computational Linguistics, Stroudsburg (1998)Google Scholar
  8. 8.
    Lovász, L., Plummer, M.: Matching Theory. Akadémiai Kiadó, Budapest (1986)zbMATHGoogle Scholar
  9. 9.
    Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)CrossRefzbMATHGoogle Scholar
  10. 10.
    Porter, M.F.: An algorithm for suffix stripping. Program: Electron. Lib. 14(3), 130–137 (1980)CrossRefGoogle Scholar
  11. 11.
    Schrammel, J., Leitner, M., Tscheligi, M.: Semantically structured tag clouds: An empirical evaluation of clustered presentation approaches. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 2037–2040. ACM, New York (2009)Google Scholar
  12. 12.
    Viégas, F.B., Wattenberg, M., Feinberg, J.: Participatory visualization with Wordle. IEEE Trans. Vis. Comput. Graphics 15(6), 1137–1144 (2009)CrossRefGoogle Scholar
  13. 13.
    Wu, Y., Provan, T., Wei, F., Liu, S., Ma, K.L.: Semantic-preserving word clouds by seam carving. Comput. Graph. Forum 30(3), 741–750 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lukas Barth
    • 1
  • Stephen G. Kobourov
    • 2
  • Sergey Pupyrev
    • 2
    • 3
  1. 1.Institute of Theoretical InformaticsKarlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Department of Computer ScienceUniversity of ArizonaTucsonUSA
  3. 3.Institute of Mathematics and Computer ScienceUral Federal UniversityEkaterinburgRussia

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