Name
Abstract | ||
|---|---|---|
In computer-based literary analysis different types of features are used to characterize a text. Usually, only a single feature value or vector is calculated for the whole text. In this paper, we combine automatic literature analysis methods with an effective visualization technique to analyze the behavior of the feature values across the text. For an interactive visual analysis, we calculate a sequence of feature values per text and present them to the user as a characteristic fingerprint. The feature values may be calculated on different hierarchy levels, allowing the analysis to be done on different resolution levels. A case study shows several successful applications of our new method to known literature problems and demonstrates the advantage of our new visual literature fingerprinting. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/VAST.2007.4389004 | Virtual reality, archeology, and cultural heritage |
Keywords | Field | DocType |
new method,literature fingerprinting,i.6.9 visualization: infor- mation visualization—visualization techniques and methodolo- gies,visual analytics,literature,feature value,different type,literature fingerprinting index terms: j.5 computer applications: arts and humanities—linguistics,known literature problem,visual literary analysis,different resolution level,visual literature analysis,whole text,computer-based literary analysis,interactive visual analysis,different hierarchy level,automatic literature analysis method,single feature value,data visualisation,indexing terms,interactive visualization | Computer aided instruction,Data visualization,Computer science,Visualization,Visual analytics,Fingerprint,Interactive visual analysis,Natural language processing,Artificial intelligence,Hierarchy | Conference |
ISSN | Citations | PageRank |
2325-9442 | 38 | 1.47 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel A. Keim | 1 | 7704 | 1141.60 |
| Daniela Oelke | 2 | 225 | 13.18 |