Publikation: WordSpace Visual Summary of Text Corpora
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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.
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BRANDES, Ulrik, Martin HOEFER, Jürgen LERNER, 2006. WordSpace Visual Summary of Text Corpora. Electronic Imaging 2006. San Jose, CA. In: ERBACHER, Robert F., ed., Jonathan C. ROBERTS, ed., Matti T. GRÖHN, ed., Katy BÖRNER, ed.. Visualization and Data Analysis 2006. SPIE, 2006, 60600N. SPIE Proceedings. 6060. Available under: doi: 10.1117/12.647867BibTex
@inproceedings{Brandes2006-01-15WordS-5810, year={2006}, doi={10.1117/12.647867}, title={WordSpace Visual Summary of Text Corpora}, number={6060}, publisher={SPIE}, series={SPIE Proceedings}, booktitle={Visualization and Data Analysis 2006}, editor={Erbacher, Robert F. and Roberts, Jonathan C. and Gröhn, Matti T. and Börner, Katy}, author={Brandes, Ulrik and Hoefer, Martin and Lerner, Jürgen}, note={Article Number: 60600N} }
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