WordSpace: visual summary of text corpora

Ulrik Brandes; Martin Hoefer; Jürgen Lerner

doi:10.1117/12.647867

16 January 2006 WordSpace: visual summary of text corpora

Ulrik Brandes, Martin Hoefer, Jürgen Lerner

Proceedings Volume 6060, Visualization and Data Analysis 2006; 60600N (2006) https://doi.org/10.1117/12.647867
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

Abstract

In recent years several well-known approaches to visualize the topical structure of a document collection have been proposed. Most of them feature spectral analysis of a term-document matrix with influence values and dimensionality reduction. We generalize this approach by arguing that there are many reasonable ways to project the term-document matrix into low-dimensional space in which different features of the corpus are emphasized. Our main tool is a continuous generalization of adjacency-respecting partitions called structural similarity. In this way we obtain a generic framework in which influence weights in the term-document matrix, dimensionality-reducing projections, and the display of a target subspace may be varied according to nature of the text corpus.

Citation Download Citation

Ulrik Brandes, Martin Hoefer, and Jürgen Lerner "WordSpace: visual summary of text corpora", Proc. SPIE 6060, Visualization and Data Analysis 2006, 60600N (16 January 2006); https://doi.org/10.1117/12.647867

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