The shape of Shakespeare: visualizing text using implicit surfaces

Rohrer, Randall M.; Ebert, Dylan; Sibert, John L.

doi:10.1109/infvis.1998.729568

“…One approach maps keywords to basis vectors, which are used to create a 3-D blob for each document; blobs with similar features should have similar content (Rohner, 1998). ThemeView (formerly ThemeScape) identifies topics within a corpus and produces a relief map; similar themes are adjacent and dominant themes are higher (Wise, 1995).…”

Section: Related Workmentioning

confidence: 99%

What Do You Do with a Million Books?

Crane¹

2006

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This paper describes a system to support humanities scholars in their interpretation of literary work. It presents a user interface and web architecture that integrates text mining, a graphical user interface and visualization, while attempting to remain easy to use by non specialists. Users can interactively read and rate documents found in a digital libraries collection, prepare training sets, review results of classification algorithms and explore possible indicators and explanations. Initial evaluation steps suggest that there is a rationale for "provocational" text mining in literary interpretation.

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“…Other text visualizations focus on keywords as a means of reducing the data. One approach maps keywords to basis vectors, which are used to create a 3-D blob for each document; blobs with similar features should have similar content [26]. ThemeView (formerly ThemeScape) identifies topics within a corpus and produces a relief map; similar themes are adjacent and dominant themes are higher [36].…”

Section: Related Workmentioning

confidence: 99%

Exploring erotics in Emily Dickinson's correspondence with text mining and visual interfaces

Plaisant

¹

,

Rose

²

,

Yu

³

et al. 2006

Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries

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This paper describes a system to support humanities scholars in their interpretation of literary work. It presents a user interface and web architecture that integrates text mining, a graphical user interface and visualization, while attempting to remain easy to use by non specialists. Users can interactively read and rate documents found in a digital libraries collection, prepare training sets, review results of classification algorithms and explore possible indicators and explanations. Initial evaluation steps suggest that there is a rationale for "provocational" text mining in literary interpretation.

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“…The visualization of text has been proposed to help navigate digital libraries, including galaxies visualization [16], mapping text to surfaces [17], principal components analysis [18], multiple views [19], and self-organizing maps [20]. The purpose is to visualize the relationship between different documents and not express aspects of the document contents per se.…”

Section: Introductionmentioning

confidence: 99%