Abstract
Since their appearance Tag Clouds are widely used tools in Internet. The main purposes of these textual visualizations are information retrieval, content representation and browsing of text. Despite their widespread use and the large number of research that has been carried out on them, the main metrics available in the literature evaluate the quality of the tag cloud based only on the query results. There are no adequate metrics when the tag cloud is extracted from text and used to represent information content. In this work, three new metrics are proposed for the evaluation of tag clouds when their main function is to represent information content: coverage, overlap and disparity, as well as a fourth metric: the balance, in which we propose a way to calculate it by using OWA operators.
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https://www.filmaffinity.com/, last accessed March 2018.
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Acknowledgements
This work has been partially supported by the “Plan Andaluz de Investigación, Junta de Andalucía” (Spain) under research project P10- TIC6019.
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Torres-Parejo, Ú., Campaña, J.R., Vila, MA., Delgado, M. (2018). Metrics for Tag Cloud Evaluation. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-91473-2_25
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DOI: https://doi.org/10.1007/978-3-319-91473-2_25
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