Navegando por Autor "Paulovich, Fernando Vieira"

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    Fast content-based visual mapping for interactive exploration of document collections.
    (2005-06) Minghim, Rosane; Paulovich, Fernando Vieira; Lopes, Alneu de Andrade
    This paper presents a fast technique for map generation of document collections that, besides being able to group (and separate) documents by their contents, runs at very manageable computational costs, generating maps of preprocessed text in a matter of seconds. Based on multi-dimensional projection techniques and an algorithm for projection improvement, it results in a surface map that allows the user to identify a number of important relationships between documents and groups of documents that are reflected as visual attributes such as height, color, isolines as well as aural attributes (such as pitch). The map is interactive, allowing further exploration and narrowing of focus on a search task. The technique, named IDMAP (Interactive Document Map), is fully described in this paper. The results are bound to support a large number of applications that rely on retrieval and examination of document collections.
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    Visual mapping of text collections using an approximation of Kolmogorov complexity.
    (2005-06) Telles, Guilllerme P.; Minghim, Rosane; Paulovich, Fernando Vieira
    The generation of content-based text maps is an important issue to support exploration of information and to help find relevant reading material in increasingly complex document databases. Most techniques that help relate or visualize texts rely on a vector representation that is, at its best, ad-hoc as to its parameterization. This paper presents a novel approach capable of generating a map of documents without the painstaking pre-processing steps, by comparing text against text through an approximation of the Kolmogorov complexity. The similarity measure taken from that analysis is then used to map data in 2D by applying fast multidimensional projection techniques (instead of dimensionality reduction or random initial point placement). The resulting maps show a high degree of content separation and good grouping of similar documents. The approach can be used to map text collections in a variety of applications and the map can be interacted with to further explore text groups. By avoiding vector representation our technique decreases the bias characteristic of that approach and the need for user knowledge of the process. The approach also lends itself to incremental processing for reduction of computational costs.
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    Visual mapping of text collections using an approximation of Kolmogorov complexity.
    (2005-06) Telles, Guilheme P.; Minghim, Rosane; Paulovich, Fernando Vieira
    The generation of content-based text maps is an important issue to support exploration of information and to help find relevant reading material in increasingly complex document databases. Most techniques that help relate or visualize texts rely on a vector representation that is, at its best, ad-hoc as to its parameterization. This paper presents a novel approach capable of generating a map of documents without the painstaking pre-processing steps, by comparing text against text through an approximation of the Kolmogorov complexity. The similarity measure taken from that analysis is then used to map data in 2D by applying fast multidimensional projection techniques (instead of dimensionality reduction or random initial point placement). The resulting maps show a high degree of content separation and good grouping of similar documents. The approach can be used to map text collections in a variety of applications and the map can be interacted with to further explore text groups. By avoiding vector representation our technique decreases the bias characteristic of that approach and the need for user knowledge of the process. The approach also lends itself to incremental processing for reduction of computational costs.