## Literature Fingerprinting : A New Method for Visual Literary Analysis

2007
##### Publication type
Contribution to a conference collection
##### Published in
2007 IEEE Symposium on Visual Analytics Science and Technology. - IEEE, 2007. - pp. 115-122. - ISBN 978-1-4244-1659-2
##### 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.
##### Subject (DDC)
004 Computer Science
##### Keywords
Visual literature analysis,visual analytics,literature fingerprinting
##### Conference
2007 IEEE Symposium on Visual Analytics Science and Technology, Oct 30, 2007 - Nov 1, 2007, Sacramento, CA, USA
##### Cite This
ISO 690KEIM, Daniel A., Daniela OELKE, 2007. Literature Fingerprinting : A New Method for Visual Literary Analysis. 2007 IEEE Symposium on Visual Analytics Science and Technology. Sacramento, CA, USA, Oct 30, 2007 - Nov 1, 2007. In: 2007 IEEE Symposium on Visual Analytics Science and Technology. IEEE, pp. 115-122. ISBN 978-1-4244-1659-2. Available under: doi: 10.1109/VAST.2007.4389004
BibTex
@inproceedings{Keim2007-10Liter-5492,
year={2007},
doi={10.1109/VAST.2007.4389004},
title={Literature Fingerprinting : A New Method for Visual Literary Analysis},
isbn={978-1-4244-1659-2},
publisher={IEEE},
booktitle={2007 IEEE Symposium on Visual Analytics Science and Technology},
pages={115--122},
author={Keim, Daniel A. and Oelke, Daniela}
}

RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dc:creator>Keim, Daniel A.</dc:creator>
<dc:contributor>Oelke, Daniela</dc:contributor>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5492/1/Literature_Fingerprinting.pdf"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5492"/>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5492/1/Literature_Fingerprinting.pdf"/>
<dc:language>eng</dc:language>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dcterms:bibliographicCitation>First publ. in: IEEE Symposium on Visual Analytics Science and Technology (VAST 2007),Sacramento, CA, USA, October 30 - November 1, 2007, pp. 115-122</dcterms:bibliographicCitation>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:50Z</dcterms:available>
<dcterms:title>Literature Fingerprinting : A New Method for Visual Literary Analysis</dcterms:title>
<dc:format>application/pdf</dc:format>
<dc:creator>Oelke, Daniela</dc:creator>
<dcterms:abstract xml:lang="eng">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.</dcterms:abstract>