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Knowledge and Information Systems

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01.08.2014 | Regular Paper

A theoretical model for the automatic generation of tag clouds

verfasst von: Ursula Torres-Parejo, Jesús R. Campaña, M. Amparo Vila, Miguel Delgado

Erschienen in: Knowledge and Information Systems | Ausgabe 2/2014

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Abstract

This paper presents a new approach to information retrieval from non-structured attributes in databases, which involves the processing of text attributes. To make retrieval more effective, frequent text sequences are extracted and mathematically represented as intermediate forms which permit a clearer and more precise definition of operations on texts. These intermediate forms appear to users in the form of tag clouds to facilitate content identification, exploration, and querying. In this sense, tag cloud visualization is a simple, user-friendly visual interface to data. This paper proposes a theoretical model for the representation of frequent text sequences and their operations as well as a general procedure for generating tag clouds from text attributes in databases. The tag clouds thus obtained were compared with conventional tag clouds composed of single terms. Our study showed that automatically generated multi-term tag clouds provide better results than mono-term tag clouds.

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http://nlp.stanford.edu/software/tagger.shtml.

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Titel: A theoretical model for the automatic generation of tag clouds
verfasst von: Ursula Torres-Parejo
Jesús R. Campaña
M. Amparo Vila
Miguel Delgado
Publikationsdatum: 01.08.2014
Verlag: Springer London
Erschienen in: Knowledge and Information Systems / Ausgabe 2/2014
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI: https://doi.org/10.1007/s10115-013-0651-9

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